More on Productivity
Asher Umerie
3 years ago
What is Bionic Reading?
Senses help us navigate a complicated world. They shape our worldview - how we hear, smell, feel, and taste. People claim a sixth sense, an intuitive capacity that extends perception.
Our brain is a half-pool of grey and white matter that stores data from our senses. Brains provide us context, so zombies' obsession makes sense.
Bionic reading uses the brain's visual information and context to simplify text comprehension.
Stay with me.
What is Bionic Reading?
Bionic reading is a software application established by Swiss typographic designer Renato Casutt. The term honors the brain (bio) and technology's collaboration to better text comprehension.
The image above shows two similar paragraphs with bionic reading.
Notice anything yet?
This Twitter user did.
I did too...
Image text describes bionic reading-
New method to aid reading by using artificial fixation points. The reader focuses on the highlighted starting letters, and the brain completes the word.
How is Bionic Reading possible?
Do you remember seeing social media posts asking you to stare at a black dot for 30 seconds (or more)? You blink and see an after-image on your wall.
Our brains are skilled at identifying patterns and'seeing' familiar objects, therefore optical illusions are conceivable.
Brain and sight collaborate well. Text comprehension proves it.
Considering evolutionary patterns, humans' understanding skills may be cosmic luck.
Scientists don't know why people can read and write, but they do know what reading does to the brain.
One portion of your brain recognizes words, while another analyzes their meaning. Fixation, saccade, and linguistic transparency/opacity aid.
Let's explain some terms.
-
Fixation is how the eyes move when reading. It's where you look. If the eyes fixate less, a reader can read quicker. [Eye fixation is a physiological process](Eye fixation is a naturally occurring physiological process) impacted by the reader's vocabulary, vision span, and text familiarity.
-
Saccade - Pause and look around. That's a saccade. Rapid eye movements that alter the place of fixation, as reading text or looking around a room. They can happen willingly (when you choose) or instinctively, even when your eyes are fixed.
-
Linguistic transparency and opacity analyze how well a composite word or phrase may be deduced from its constituents.
The Bionic reading website compares these tools.
Text highlights lead the eye. Fixation, saccade, and opacity can transfer visual stimuli to text, changing typeface.
## Final Thoughts on Bionic Reading
I'm excited about how this could influence my long-term assimilation and productivity.
This technology is still in development, with prototypes working on only a few apps. Like any new tech, it will be criticized.
I'll be watching Bionic Reading closely. Comment on it!
Leonardo Castorina
3 years ago
How to Use Obsidian to Boost Research Productivity
Tools for managing your PhD projects, reading lists, notes, and inspiration.
As a researcher, you have to know everything. But knowledge is useless if it cannot be accessed quickly. An easy-to-use method of archiving information makes taking notes effortless and enjoyable.
As a PhD student in Artificial Intelligence, I use Obsidian (https://obsidian.md) to manage my knowledge.
The article has three parts:
- What is a note, how to organize notes, tags, folders, and links? This section is tool-agnostic, so you can use most of these ideas with any note-taking app.
- Instructions for using Obsidian, managing notes, reading lists, and useful plugins. This section demonstrates how I use Obsidian, my preferred knowledge management tool.
- Workflows: How to use Zotero to take notes from papers, manage multiple projects' notes, create MOCs with Dataview, and more. This section explains how to use Obsidian to solve common scientific problems and manage/maintain your knowledge effectively.
This list is not perfect or complete, but it is my current solution to problems I've encountered during my PhD. Please leave additional comments or contact me if you have any feedback. I'll try to update this article.
Throughout the article, I'll refer to your digital library as your "Obsidian Vault" or "Zettelkasten".
Other useful resources are listed at the end of the article.
1. Philosophy: Taking and organizing notes
Carl Sagan: “To make an apple pie from scratch, you must first create the universe.”
Before diving into Obsidian, let's establish a Personal Knowledge Management System and a Zettelkasten. You can skip to Section 2 if you already know these terms.
Niklas Luhmann, a prolific sociologist who wrote 400 papers and 70 books, inspired this section and much of Zettelkasten. Zettelkasten means “slip box” (or library in this article). His Zettlekasten had around 90000 physical notes, which can be found here.
There are now many tools available to help with this process. Obsidian's website has a good introduction section: https://publish.obsidian.md/hub/
Notes
We'll start with "What is a note?" Although it may seem trivial, the answer depends on the topic or your note-taking style. The idea is that a note is as “atomic” (i.e. You should read the note and get the idea right away.
The resolution of your notes depends on their detail. Deep Learning, for example, could be a general description of Neural Networks, with a few notes on the various architectures (eg. Recurrent Neural Networks, Convolutional Neural Networks etc..).
Limiting length and detail is a good rule of thumb. If you need more detail in a specific section of this note, break it up into smaller notes. Deep Learning now has three notes:
- Deep Learning
- Recurrent Neural Networks
- Convolutional Neural Networks
Repeat this step as needed until you achieve the desired granularity. You might want to put these notes in a “Neural Networks” folder because they are all about the same thing. But there's a better way:
#Tags and [[Links]] over /Folders/
The main issue with folders is that they are not flexible and assume that all notes in the folder belong to a single category. This makes it difficult to make connections between topics.
Deep Learning has been used to predict protein structure (AlphaFold) and classify images (ImageNet). Imagine a folder structure like this:
- /Proteins/
- Protein Folding
- /Deep Learning/
- /Proteins/
Your notes about Protein Folding and Convolutional Neural Networks will be separate, and you won't be able to find them in the same folder.
This can be solved in several ways. The most common one is to use tags rather than folders. A note can be grouped with multiple topics this way. Obsidian tags can also be nested (have subtags).
You can also link two notes together. You can build your “Knowledge Graph” in Obsidian and other note-taking apps like Obsidian.
My Knowledge Graph. Green: Biology, Red: Machine Learning, Yellow: Autoencoders, Blue: Graphs, Brown: Tags.
My Knowledge Graph and the note “Backrpropagation” and its links.
Backpropagation note and all its links
Why use Folders?
Folders help organize your vault as it grows. The main suggestion is to have few folders that "weakly" collect groups of notes or better yet, notes from different sources.
Among my Zettelkasten folders are:
My Zettelkasten's 5 folders
They usually gather data from various sources:
MOC: Map of Contents for the Zettelkasten.
Projects: Contains one note for each side-project of my PhD where I log my progress and ideas. Notes are linked to these.
Bio and ML: These two are the main content of my Zettelkasten and could theoretically be combined.
Papers: All my scientific paper notes go here. A bibliography links the notes. Zotero .bib file
Books: I make a note for each book I read, which I then split into multiple notes.
Keeping images separate from other files can help keep your main folders clean.
I will elaborate on these in the Workflow Section.
My general recommendation is to use tags and links instead of folders.
Maps of Content (MOC)
Making Tables of Contents is a good solution (MOCs).
These are notes that "signposts" your Zettelkasten library, directing you to the right type of notes. It can link to other notes based on common tags. This is usually done with a title, then your notes related to that title. As an example:
An example of a Machine Learning MOC generated with Dataview.
As shown above, my Machine Learning MOC begins with the basics. Then it's on to Variational Auto-Encoders. Not only does this save time, but it also saves scrolling through the tag search section.
So I keep MOCs at the top of my library so I can quickly find information and see my library. These MOCs are generated automatically using an Obsidian Plugin called Dataview (https://github.com/blacksmithgu/obsidian-dataview).
Ideally, MOCs could be expanded to include more information about the notes, their status, and what's left to do. In the absence of this, Dataview does a fantastic job at creating a good structure for your notes.
In the absence of this, Dataview does a fantastic job at creating a good structure for your notes.
2. Tools: Knowing Obsidian
Obsidian is my preferred tool because it is free, all notes are stored in Markdown format, and each panel can be dragged and dropped. You can get it here: https://obsidian.md/
Obsidian interface.
Obsidian is highly customizable, so here is my preferred interface:
The theme is customized from https://github.com/colineckert/obsidian-things
Alternatively, each panel can be collapsed, moved, or removed as desired. To open a panel later, click on the vertical "..." (bottom left of the note panel).
My interface is organized as follows:
How my Obsidian Interface is organized.
Folders/Search:
This is where I keep all relevant folders. I usually use the MOC note to navigate, but sometimes I use the search button to find a note.
Tags:
I use nested tags and look into each one to find specific notes to link.
cMenu:
Easy-to-use menu plugin cMenu (https://github.com/chetachiezikeuzor/cMenu-Plugin)
Global Graph:
The global graph shows all your notes (linked and unlinked). Linked notes will appear closer together. Zoom in to read each note's title. It's a bit overwhelming at first, but as your library grows, you get used to the positions and start thinking of new connections between notes.
Local Graph:
Your current note will be shown in relation to other linked notes in your library. When needed, you can quickly jump to another link and back to the current note.
Links:
Finally, an outline panel and the plugin Obsidian Power Search (https://github.com/aviral-batra/obsidian-power-search) allow me to search my vault by highlighting text.
Start using the tool and worry about panel positioning later. I encourage you to find the best use-case for your library.
Plugins
An additional benefit of using Obsidian is the large plugin library. I use several (Calendar, Citations, Dataview, Templater, Admonition):
Obsidian Calendar Plugin: https://github.com/liamcain
It organizes your notes on a calendar. This is ideal for meeting notes or keeping a journal.
Calendar addon from hans/obsidian-citation-plugin
Obsidian Citation Plugin: https://github.com/hans/
Allows you to cite papers from a.bib file. You can also customize your notes (eg. Title, Authors, Abstract etc..)
Plugin citation from hans/obsidian-citation-plugin
Obsidian Dataview: https://github.com/blacksmithgu/
A powerful plugin that allows you to query your library as a database and generate content automatically. See the MOC section for an example.
Allows you to create notes with specific templates like dates, tags, and headings.
Templater. Obsidian Admonition: https://github.com/valentine195/obsidian-admonition
Blocks allow you to organize your notes.
Plugin warning. Obsidian Admonition (valentine195)
There are many more, but this list should get you started.
3. Workflows: Cool stuff
Here are a few of my workflows for using obsidian for scientific research. This is a list of resources I've found useful for my use-cases. I'll outline and describe them briefly so you can skim them quickly.
3.1 Using Templates to Structure Notes
3.2 Free Note Syncing (Laptop, Phone, Tablet)
3.3 Zotero/Mendeley/JabRef -> Obsidian — Managing Reading Lists
3.4 Projects and Lab Books
3.5 Private Encrypted Diary
3.1 Using Templates to Structure Notes
Plugins: Templater and Dataview (optional).
To take effective notes, you must first make adding new notes as easy as possible. Templates can save you time and give your notes a consistent structure. As an example:
An example of a note using a template.
### [[YOUR MOC]]
# Note Title of your note
**Tags**::
**Links**::
The top line links to your knowledge base's Map of Content (MOC) (see previous sections). After the title, I add tags (and a link between the note and the tag) and links to related notes.
To quickly identify all notes that need to be expanded, I add the tag “#todo”. In the “TODO:” section, I list the tasks within the note.
The rest are notes on the topic.
Templater can help you create these templates. For new books, I use the following template:
### [[Books MOC]]
# Title
**Author**::
**Date::
**Tags::
**Links::
A book template example.
Using a simple query, I can hook Dataview to it.
dataview
table author as Author, date as “Date Finished”, tags as “Tags”, grade as “Grade”
from “4. Books”
SORT grade DESCENDING
using Dataview to query templates.
3.2 Free Note Syncing (Laptop, Phone, Tablet)
No plugins used.
One of my favorite features of Obsidian is the library's self-contained and portable format. Your folder contains everything (plugins included).
Ordinary folders and documents are available as well. There is also a “.obsidian” folder. This contains all your plugins and settings, so you can use it on other devices.
So you can use Google Drive, iCloud, or Dropbox for free as long as you sync your folder (note: your folder should be in your Cloud Folder).
For my iOS and macOS work, I prefer iCloud. You can also use the paid service Obsidian Sync.
3.3 Obsidian — Managing Reading Lists and Notes in Zotero/Mendeley/JabRef
Plugins: Quotes (required).
3.3 Zotero/Mendeley/JabRef -> Obsidian — Taking Notes and Managing Reading Lists of Scientific Papers
My preferred reference manager is Zotero, but this workflow should work with any reference manager that produces a .bib file. This file is exported to my cloud folder so I can access it from any platform.
My Zotero library is tagged as follows:
My reference manager's tags
For readings, I usually search for the tags “!!!” and “To-Read” and select a paper. Annotate the paper next (either on PDF using GoodNotes or on physical paper).
Then I make a paper page using a template in the Citations plugin settings:
An example of my citations template.
Create a new note, open the command list with CMD/CTRL + P, and find the Citations “Insert literature note content in the current pane” to see this lovely view.
Citation generated by the article https://doi.org/10.1101/2022.01.24.22269144
You can then convert your notes to digital. I found that transcribing helped me retain information better.
3.4 Projects and Lab Books
Plugins: Tweaker (required).
PhD students offering advice on thesis writing are common (read as regret). I started asking them what they would have done differently or earlier.
“Deep stuff Leo,” one person said. So my main issue is basic organization, losing track of my tasks and the reasons for them.
As a result, I'd go on other experiments that didn't make sense, and have to reverse engineer my logic for thesis writing. - PhD student now wise Postdoc
Time management requires planning. Keeping track of multiple projects and lab books is difficult during a PhD. How I deal with it:
- One folder for all my projects
- One file for each project
I use a template to create each project
### [[Projects MOC]]
# <% tp.file.title %>
**Tags**::
**Links**::
**URL**::
**Project Description**::## Notes:
### <% tp.file.last_modified_date(“dddd Do MMMM YYYY”) %>
#### Done:
#### TODO:
#### Notes
You can insert a template into a new note with CMD + P and looking for the Templater option.
I then keep adding new days with another template:
### <% tp.file.last_modified_date("dddd Do MMMM YYYY") %>
#### Done:
#### TODO:
#### Notes:
This way you can keep adding days to your project and update with reasonings and things you still have to do and have done. An example below:
Example of project note with timestamped notes.
3.5 Private Encrypted Diary
This is one of my favorite Obsidian uses.
Mini Diary's interface has long frustrated me. After the author archived the project, I looked for a replacement. I had two demands:
- It had to be private, and nobody had to be able to read the entries.
- Cloud syncing was required for editing on multiple devices.
Then I learned about encrypting the Obsidian folder. Then decrypt and open the folder with Obsidian. Sync the folder as usual.
Use CryptoMator (https://cryptomator.org/). Create an encrypted folder in Cryptomator for your Obsidian vault, set a password, and let it do the rest.
If you need a step-by-step video guide, here it is:
Conclusion
So, I hope this was helpful!
In the first section of the article, we discussed notes and note-taking techniques. We discussed when to use tags and links over folders and when to break up larger notes.
Then we learned about Obsidian, its interface, and some useful plugins like Citations for citing papers and Templater for creating note templates.
Finally, we discussed workflows and how to use Zotero to take notes from scientific papers, as well as managing Lab Books and Private Encrypted Diaries.
Thanks for reading and commenting :)
Read original post here
Cammi Pham
3 years ago
7 Scientifically Proven Things You Must Stop Doing To Be More Productive
Smarter work yields better results.
17-year-old me worked and studied 20 hours a day. During school breaks, I did coursework and ran a nonprofit at night. Long hours earned me national campaigns, A-list opportunities, and a great career. As I aged, my thoughts changed. Working harder isn't necessarily the key to success.
In some cases, doing less work might lead to better outcomes.
Consider a hard-working small business owner. He can't beat his corporate rivals by working hard. Time's limited. An entrepreneur can work 24 hours a day, 7 days a week, but a rival can invest more money, create a staff, and put in more man hours. Why have small startups done what larger companies couldn't? Facebook paid $1 billion for 13-person Instagram. Snapchat, a 30-person startup, rejected Facebook and Google bids. Luck and efficiency each contributed to their achievement.
The key to success is not working hard. It’s working smart.
Being busy and productive are different. Busy doesn't always equal productive. Productivity is less about time management and more about energy management. Life's work. It's using less energy to obtain more rewards. I cut my work week from 80 to 40 hours and got more done. I value simplicity.
Here are seven activities I gave up in order to be more productive.
1. Give up working extra hours and boost productivity instead.
When did the five-day, 40-hour work week start? Henry Ford, Ford Motor Company founder, experimented with his workers in 1926.
He decreased their daily hours from 10 to 8, and shortened the work week from 6 days to 5. As a result, he saw his workers’ productivity increase.
According to a 1980 Business Roundtable report, Scheduled Overtime Effect on Construction Projects, the more you work, the less effective and productive you become.
“Where a work schedule of 60 or more hours per week is continued longer than about two months, the cumulative effect of decreased productivity will cause a delay in the completion date beyond that which could have been realized with the same crew size on a 40-hour week.” Source: Calculating Loss of Productivity Due to Overtime Using Published Charts — Fact or Fiction
AlterNet editor Sara Robinson cited US military research showing that losing one hour of sleep per night for a week causes cognitive impairment equivalent to a.10 blood alcohol level. You can get fired for showing up drunk, but an all-nighter is fine.
Irrespective of how well you were able to get on with your day after that most recent night without sleep, it is unlikely that you felt especially upbeat and joyous about the world. Your more-negative-than-usual perspective will have resulted from a generalized low mood, which is a normal consequence of being overtired. More important than just the mood, this mind-set is often accompanied by decreases in willingness to think and act proactively, control impulses, feel positive about yourself, empathize with others, and generally use emotional intelligence. Source: The Secret World of Sleep: The Surprising Science of the Mind at Rest
To be productive, don't overwork and get enough sleep. If you're not productive, lack of sleep may be to blame. James Maas, a sleep researcher and expert, said 7/10 Americans don't get enough sleep.
Did you know?
Leonardo da Vinci slept little at night and frequently took naps.
Napoleon, the French emperor, had no qualms about napping. He splurged every day.
Even though Thomas Edison felt self-conscious about his napping behavior, he regularly engaged in this ritual.
President Franklin D. Roosevelt's wife Eleanor used to take naps before speeches to increase her energy.
The Singing Cowboy, Gene Autry, was known for taking regular naps in his dressing area in between shows.
Every day, President John F. Kennedy took a siesta after eating his lunch in bed.
Every afternoon, oil businessman and philanthropist John D. Rockefeller took a nap in his office.
It was unavoidable for Winston Churchill to take an afternoon snooze. He thought it enabled him to accomplish twice as much each day.
Every afternoon around 3:30, President Lyndon B. Johnson took a nap to divide his day into two segments.
Ronald Reagan, the 40th president, was well known for taking naps as well.
Source: 5 Reasons Why You Should Take a Nap Every Day — Michael Hyatt
Since I started getting 7 to 8 hours of sleep a night, I've been more productive and completed more work than when I worked 16 hours a day. Who knew marketers could use sleep?
2. Refrain from accepting too frequently
Pareto's principle states that 20% of effort produces 80% of results, but 20% of results takes 80% of effort. Instead of working harder, we should prioritize the initiatives that produce the most outcomes. So we can focus on crucial tasks. Stop accepting unproductive tasks.
“The difference between successful people and very successful people is that very successful people say “no” to almost everything.” — Warren Buffett
What should you accept? Why say no? Consider doing a split test to determine if anything is worth your attention. Track what you do, how long it takes, and the consequences. Then, evaluate your list to discover what worked (or didn't) to optimize future chores.
Most of us say yes more often than we should, out of guilt, overextension, and because it's simpler than no. Nobody likes being awful.
Researchers separated 120 students into two groups for a 2012 Journal of Consumer Research study. One group was educated to say “I can't” while discussing choices, while the other used “I don't”.
The students who told themselves “I can’t eat X” chose to eat the chocolate candy bar 61% of the time. Meanwhile, the students who told themselves “I don’t eat X” chose to eat the chocolate candy bars only 36% of the time. This simple change in terminology significantly improved the odds that each person would make a more healthy food choice.
Next time you need to say no, utilize I don't to encourage saying no to unimportant things.
The 20-second rule is another wonderful way to avoid pursuits with little value. Add a 20-second roadblock to things you shouldn't do or bad habits you want to break. Delete social media apps from your phone so it takes you 20 seconds to find your laptop to access them. You'll be less likely to engage in a draining hobby or habit if you add an inconvenience.
Lower the activation energy for habits you want to adopt and raise it for habits you want to avoid. The more we can lower or even eliminate the activation energy for our desired actions, the more we enhance our ability to jump-start positive change. Source: The Happiness Advantage: The Seven Principles of Positive Psychology That Fuel Success and Performance at Work
3. Stop doing everything yourself and start letting people help you
I once managed a large community and couldn't do it alone. The community took over once I burned out. Members did better than I could have alone. I learned about community and user-generated content.
Consumers know what they want better than marketers. Octoly says user-generated videos on YouTube are viewed 10 times more than brand-generated videos. 51% of Americans trust user-generated material more than a brand's official website (16%) or media coverage (22%). (14 percent). Marketers should seek help from the brand community.
Being a successful content marketer isn't about generating the best content, but cultivating a wonderful community.
We should seek aid when needed. We can't do everything. It's best to delegate work so you may focus on the most critical things. Instead of overworking or doing things alone, let others help.
Having friends or coworkers around can boost your productivity even if they can't help.
Just having friends nearby can push you toward productivity. “There’s a concept in ADHD treatment called the ‘body double,’ ” says David Nowell, Ph.D., a clinical neuropsychologist from Worcester, Massachusetts. “Distractable people get more done when there is someone else there, even if he isn’t coaching or assisting them.” If you’re facing a task that is dull or difficult, such as cleaning out your closets or pulling together your receipts for tax time, get a friend to be your body double. Source: Friendfluence: The Surprising Ways Friends Make Us Who We Are
4. Give up striving for perfection
Perfectionism hinders professors' research output. Dr. Simon Sherry, a psychology professor at Dalhousie University, did a study on perfectionism and productivity. Dr. Sherry established a link between perfectionism and productivity.
Perfectionism has its drawbacks.
They work on a task longer than necessary.
They delay and wait for the ideal opportunity. If the time is right in business, you are already past the point.
They pay too much attention to the details and miss the big picture.
Marketers await the right time. They miss out.
The perfect moment is NOW.
5. Automate monotonous chores instead of continuing to do them.
A team of five workers who spent 3%, 20%, 25%, 30%, and 70% of their time on repetitive tasks reduced their time spent to 3%, 10%, 15%, 15%, and 10% after two months of working to improve their productivity.
Last week, I wrote a 15-minute Python program. I wanted to generate content utilizing Twitter API data and Hootsuite to bulk schedule it. Automation has cut this task from a day to five minutes. Whenever I do something more than five times, I try to automate it.
Automate monotonous chores without coding. Skills and resources are nice, but not required. If you cannot build it, buy it.
People forget time equals money. Manual work is easy and requires little investigation. You can moderate 30 Instagram photographs for your UGC campaign. You need digital asset management software to manage 30,000 photographs and movies from five platforms. Filemobile helps individuals develop more user-generated content. You may buy software to manage rich media and address most internet difficulties.
Hire an expert if you can't find a solution. Spend money to make money, and time is your most precious asset.
Visit GitHub or Google Apps Script library, marketers. You may often find free, easy-to-use open source code.
6. Stop relying on intuition and start supporting your choices with data.
You may optimize your life by optimizing webpages for search engines.
Numerous studies might help you boost your productivity. Did you know individuals are most distracted from midday to 4 p.m.? This is what a Penn State psychology professor found. Even if you can't find data on a particular question, it's easy to run a split test and review your own results.
7. Stop working and spend some time doing absolutely nothing.
Most people don't know that being too focused can be destructive to our work or achievements. The Boston Globe's The Power of Lonely says solo time is excellent for the brain and spirit.
One ongoing Harvard study indicates that people form more lasting and accurate memories if they believe they’re experiencing something alone. Another indicates that a certain amount of solitude can make a person more capable of empathy towards others. And while no one would dispute that too much isolation early in life can be unhealthy, a certain amount of solitude has been shown to help teenagers improve their moods and earn good grades in school. Source: The Power of Lonely
Reflection is vital. We find solutions when we're not looking.
We don't become more productive overnight. It demands effort and practice. Waiting for change doesn't work. Instead, learn about your body and identify ways to optimize your energy and time for a happy existence.
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Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
Non-technical talents can benefit data scientists in addition to statistics and programming.
As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.
Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.
Ready? Let’s dive in.
Best books for data scientists
1. The Black Swan
Author: Nassim Taleb
First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.
Three characteristics define a black swan event:
It is erratic.
It has a significant impact.
Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.
People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.
Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.
Try multiple tactics and models because you may find the answer.
2. High Output Management
Author: Andrew Grove
Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.
That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.
Five lessons:
Every action is a procedure.
Meetings are a medium of work
Manage short-term goals in accordance with long-term strategies.
Mission-oriented teams accelerate while functional teams increase leverage.
Utilize performance evaluations to enhance output.
So — if the above captures your imagination, it’s well worth getting stuck in.
3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
Author: Ben Horowitz
Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.
Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.
It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.
Find suggestions on:
create software
Run a business.
Promote a product
Obtain resources
Smart investment
oversee daily operations
This book will help you cope with tough times.
4. Obviously Awesome: How to Nail Product Positioning
Author: April Dunford
Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.
How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.
You'll learn:
Select the ideal market for your products.
Connect an audience to the value of your goods right away.
Take use of three positioning philosophies.
Utilize market trends to aid purchasers
5. The Mom test
Author: Rob Fitzpatrick
The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.
Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.
6. Introduction to Machine Learning with Python: A Guide for Data Scientists
Authors: Andreas C. Müller, Sarah Guido
Now, technical documents.
This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.
Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.
If you know machine learning or artificial neural networks, skip this.
7. Python Data Science Handbook: Essential Tools for Working with Data
Author: Jake VanderPlas
Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.
Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.
The only thing missing is a way to apply your learnings.
8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Author: Wes McKinney
The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.
The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.
9. Data Science from Scratch
Author: Joel Grus
Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.
The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.
Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.
10. Machine Learning Yearning
Author: Andrew Ng
Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.
The book delivers knowledge and teaches how to apply it, so you'll know how to:
Determine the optimal course of action for your ML project.
Create software that is more effective than people.
Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.
Identifying machine learning system flaws
Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.
11. Deep Learning with PyTorch Step-by-Step
Author: Daniel Voigt Godoy
The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.
It comprises four parts:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)
We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.
Is every data scientist a humanist?
Even as a technological professional, you can't escape human interaction, especially with clients.
We hope these books will help you develop interpersonal skills.
Jussi Luukkonen, MBA
3 years ago
Is Apple Secretly Building A Disruptive Tsunami?
A TECHNICAL THOUGHT
The IT giant is seeding the digital Great Renaissance.
Recently, technology has been dull.
We're still fascinated by processing speeds. Wearables are no longer an engineer's dream.
Apple has been quiet and avoided huge announcements. Slowness speaks something. Everything in the spaceship HQ seems to be turning slowly, unlike competitors around buzzwords.
Is this a sign of the impending storm?
Metas stock has fallen while Google milks dumb people. Microsoft steals money from corporations and annexes platforms like Linkedin.
Just surface bubbles?
Is Apple, one of the technology continents, pushing against all others to create a paradigm shift?
The fundamental human right to privacy
Apple's unusual remarks emphasize privacy. They incorporate it into their business models and judgments.
Apple believes privacy is a human right. There are no compromises.
This makes it hard for other participants to gain Apple's ecosystem's efficiencies.
Other players without hardware platforms lose.
Apple delivers new kidneys without rejection, unlike other software vendors. Nothing compromises your privacy.
Corporate citizenship will become more popular.
Apples have full coffers. They've started using that flow to better communities, which is great.
Apple's $2.5B home investment is one example. Google and Facebook are building or proposing to build workforce housing.
Apple's funding helps marginalized populations in more than 25 California counties, not just Apple employees.
Is this a trend, and does Apple keep giving back? Hope so.
I'm not cynical enough to suspect these investments have malicious motives.
The last frontier is the environment.
Climate change is a battle-to-win.
Long-term winners will be companies that protect the environment, turning climate change dystopia into sustainable growth.
Apple has been quietly changing its supply chain to be carbon-neutral by 2030.
“Apple is dedicated to protecting the planet we all share with solutions that are supporting the communities where we work.” Lisa Jackson, Apple’s vice president of environment.
Apple's $4.7 billion Green Bond investment will produce 1.2 gigawatts of green energy for the corporation and US communities. Apple invests $2.2 billion in Europe's green energy. In the Philippines, Thailand, Nigeria, Vietnam, Colombia, Israel, and South Africa, solar installations are helping communities obtain sustainable energy.
Apple is already carbon neutral today for its global corporate operations, and this new commitment means that by 2030, every Apple device sold will have net zero climate impact. -Apple.
Apple invests in green energy and forests to reduce its paper footprint in China and the US. Apple and the Conservation Fund are safeguarding 36,000 acres of US working forest, according to GreenBiz.
Apple's packaging paper is recycled or from sustainably managed forests.
What matters is the scale.
$1 billion is a rounding error for Apple.
These small investments originate from a tree with deep, spreading roots.
Apple's genes are anchored in building the finest products possible to improve consumers' lives.
I felt it when I switched to my iPhone while waiting for a train and had to pack my Macbook. iOS 16 dictation makes writing more enjoyable. Small change boosts productivity. Smooth transition from laptop to small screen and dictation.
Apples' tiny, well-planned steps have great growth potential for all consumers in everything they do.
There is clearly disruption, but it doesn't have to be violent
Digital channels, methods, and technologies have globalized human consciousness. One person's responsibility affects many.
Apple gives us tools to be privately connected. These technologies foster creativity, innovation, fulfillment, and safety.
Apple has invented a mountain of technologies, services, and channels to assist us adapt to the good future or combat evil forces who cynically aim to control us and ruin the environment and communities. Apple has quietly disrupted sectors for decades.
Google, Microsoft, and Meta, among others, should ride this wave. It's a tsunami, but it doesn't have to be devastating if we care, share, and cooperate with political decision-makers and community leaders worldwide.
A fresh Renaissance
Renaissance geniuses Michelangelo and Da Vinci. Different but seeing something no one else could yet see. Both were talented in many areas and could discover art in science and science in art.
These geniuses exemplified a period that changed humanity for the better. They created, used, and applied new, valuable things. It lives on.
Apple is a digital genius orchard. Wozniak and Jobs offered us fertile ground for the digital renaissance. We'll build on their legacy.
We may put our seeds there and see them bloom despite corporate greed and political ignorance.
I think the coming tsunami will illuminate our planet like the Renaissance.
William Anderson
3 years ago
When My Remote Leadership Skills Took Off
4 Ways To Manage Remote Teams & Employees
The wheels hit the ground as I landed in Rochester.
Our six-person satellite office was now part of my team.
Their manager only reported to me the day before, but I had my ticket booked ahead of time.
I had managed remote employees before but this was different. Engineers dialed into headquarters for every meeting.
So when I learned about the org chart change, I knew a strong first impression would set the tone for everything else.
I was either their boss, or their boss's boss, and I needed them to know I was committed.
Managing a fleet of satellite freelancers or multiple offices requires treating others as more than just a face behind a screen.
You must comprehend each remote team member's perspective and daily interactions.
The good news is that you can start using these techniques right now to better understand and elevate virtual team members.
1. Make Visits To Other Offices
If budgeted, visit and work from offices where teams and employees report to you. Only by living alongside them can one truly comprehend their problems with communication and other aspects of modern life.
2. Have Others Come to You
• Having remote, distributed, or satellite employees and teams visit headquarters every quarter or semi-quarterly allows the main office culture to rub off on them.
When remote team members visit, more people get to meet them, which builds empathy.
If you can't afford to fly everyone, at least bring remote managers or leaders. Hopefully they can resurrect some culture.
3. Weekly Work From Home
No home office policy?
Make one.
WFH is a team-building, problem-solving, and office-viewing opportunity.
For dial-in meetings, I started working from home on occasion.
It also taught me which teams “forget” or “skip” calls.
As a remote team member, you experience all the issues first hand.
This isn't as accurate for understanding teams in other offices, but it can be done at any time.
4. Increase Contact Even If It’s Just To Chat
Don't underestimate office banter.
Sometimes it's about bonding and trust, other times it's about business.
If you get all this information in real-time, please forward it.
Even if nothing critical is happening, call remote team members to check in and chat.
I guarantee that building relationships and rapport will increase both their job satisfaction and yours.