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:

1. Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)

2. Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)

3. Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)

4. 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.

The Traffic Light Approach to Reviewing Personal, Team and Project Development

What needs improvement? If you want to improve, you need to practice your sport, musical instrument, habit, or work project. You need to assess your progress.

Continuous improvement is the foundation of focused practice and a growth mentality. Not just individually. High-performing teams pursue improvement. Right? Why is it hard?

As a leadership coach, senior manager, and high-level athlete, I've found three key questions that may unlock high performance in individuals and teams.

Problems with Reviews

Reviewing and improving performance is crucial, however I hate seeing review sessions in my diary. I rarely respond to questionnaire pop-ups or emails. Why?

Time constrains. Requests to fill out questionnaires often state they will take 10–15 minutes, but I can think of a million other things to do with that time. Next, review overload. Businesses can easily request comments online. No matter what you buy, someone will ask for your opinion. This bombardment might make feedback seem bad, which is bad.

The problem is that we might feel that way about important things like personal growth and work performance. Managers and team leaders face a greater challenge.

When to Conduct a Review

We must be wise about reviewing things that matter to us. Timing and duration matter. Reviewing the experience as quickly as possible preserves information and sentiments. Time must be brief. The review's importance and size will determine its length. We might only take a few seconds to review our morning coffee, but we might require more time for that six-month work project.

These post-event reviews should be supplemented by periodic reflection. Journaling can help with daily reflections, but I also like to undertake personal reviews every six months on vacation or at a retreat.

As an employee or line manager, you don't want to wait a year for a performance assessment. Little and frequently is best, with a more formal and in-depth assessment (typically with a written report) in 6 and 12 months.

The Easiest Method to Conduct a Review Session

I follow Einstein's review process:

“Make things as simple as possible but no simpler.”

Thus, it should be brief but deliver the necessary feedback. Quality critique is hard to receive if the process is overly complicated or long.

I have led or participated in many review processes, from strategic overhauls of big organizations to personal goal coaching. Three key questions guide the process at either end:

• What ought to stop being done?

• What should we do going forward?

• What should we do first?

Following the Rule of 3, I compare it to traffic lights. Red, amber, and green lights:

• Red What ought should we stop?

• Amber What ought to we keep up?

• Green Where should we begin?

This approach is easy to understand and self-explanatory, however below are some examples under each area.

Red What ought should we stop?

As a team or individually, we must stop doing things to improve.

Sometimes they're bad. If we want to lose weight, we should avoid sweets. If a team culture is bad, we may need to stop unpleasant behavior like gossiping instead of having difficult conversations.

Not all things we should stop are wrong. Time matters. Since it is finite, we sometimes have to stop nice things to focus on the most important. Good to Great author Jim Collins famously said:

“Don’t let the good be the enemy of the great.”

Prioritizing requires this idea. Thus, decide what to stop to prioritize.

Amber What ought to we keep up?

Should we continue with the amber light? It helps us decide what to keep doing during review. Many items fall into this category, so focus on those that make the most progress.

Which activities have the most impact? Which behaviors create the best culture? Success-building habits?

Use these questions to find positive momentum. These are the fly-wheel motions, according to Jim Collins. The Compound Effect author Darren Hardy says:

“Consistency is the key to achieving and maintaining momentum.”

What can you do consistently to reach your goal?

Green Where should we begin?

Finally, green lights indicate new beginnings. Red/amber difficulties may be involved. Stopping a red issue may give you more time to do something helpful (in the amber).

This green space inspires creativity. Kolbs learning cycle requires active exploration to progress. Thus, it's crucial to think of new approaches, try them out, and fail if required.

This notion underpins lean start-build, up's measure, learn approach and agile's trying, testing, and reviewing. Try new things until you find what works. Thomas Edison, the lighting legend, exclaimed:

“There is a way to do it better — find it!”

Failure is acceptable, but if you want to fail forward, look back on what you've done.

John Maxwell concurred with Edison:

“Fail early, fail often, but always fail forward”

A good review procedure lets us accomplish that. To avoid failure, we must act, experiment, and reflect.

Use the traffic light system to prioritize queries. Ask:

• Red What needs to stop?

• Amber What should continue to occur?

• Green What might be initiated?

Take a moment to reflect on your day. Check your priorities with these three questions. Even if merely to confirm your direction, it's a terrific exercise!

An inspiring reading list

I'm no billionaire or hedge-fund manager. My bank account doesn't have millions. Ray Dalio's love of reading motivates me to think differently.

Here are some books recommended by Ray Dalio. Each influenced me. Hope they'll help you.

Sapiens by Yuval Noah Harari

Page Count: 512
Rating on Goodreads: 4.39

My favorite nonfiction book.

Sapiens explores human evolution. It explains how Homo Sapiens developed from hunter-gatherers to a dominant species. Amazing!

Sapiens will teach you about human history. Yuval Noah Harari has a follow-up book on human evolution.

My favorite book quotes are:

• The tendency for luxuries to turn into necessities and give rise to new obligations is one of history's few unbreakable laws.

• Happiness is not dependent on material wealth, physical health, or even community. Instead, it depends on how closely subjective expectations and objective circumstances align.

• The romantic comparison between today's industry, which obliterates the environment, and our forefathers, who coexisted well with nature, is unfounded. Homo sapiens held the record among all organisms for eradicating the most plant and animal species even before the Industrial Revolution. The unfortunate distinction of being the most lethal species in the history of life belongs to us.

The Power Of Habit by Charles Duhigg

Page Count: 375
Rating on Goodreads: 4.13

Great book: The Power Of Habit. It illustrates why habits are everything. The book explains how healthier habits can improve your life, career, and society.

The Power of Habit rocks. It's a great book on productivity. Its suggestions helped me build healthier behaviors (and drop bad ones).

Read ASAP!

My favorite book quotes are:

• Change may not occur quickly or without difficulty. However, almost any behavior may be changed with enough time and effort.

• People who exercise begin to eat better and produce more at work. They are less smokers and are more patient with friends and family. They claim to feel less anxious and use their credit cards less frequently. A fundamental habit that sparks broad change is exercise.

• Habits are strong but also delicate. They may develop independently of our awareness or may be purposefully created. They frequently happen without our consent, but they can be altered by changing their constituent pieces. They have a much greater influence on how we live than we realize; in fact, they are so powerful that they cause our brains to adhere to them above all else, including common sense.

Tribe Of Mentors by Tim Ferriss

Page Count: 561
Rating on Goodreads: 4.06

Unusual book structure. It's worth reading if you want to learn from successful people.

The book is Q&A-style. Tim questions everyone. Each chapter features a different person's life-changing advice. In the book, Pressfield, Willink, Grylls, and Ravikant are interviewed.

Amazing!

My favorite book quotes are:

• According to one's courage, life can either get smaller or bigger.

• Don't engage in actions that you are aware are immoral. The reputation you have with yourself is all that constitutes self-esteem. Always be aware.

• People mistakenly believe that focusing means accepting the task at hand. However, that is in no way what it represents. It entails rejecting the numerous other worthwhile suggestions that exist. You must choose wisely. Actually, I'm just as proud of the things we haven't accomplished as I am of what I have. Saying no to 1,000 things is what innovation is.

Interpol has issued a red alert on Terraform Labs' CEO, South Korean prosecutors said.

After the May crash of Terra Luna revealed tax evasion issues, South Korean officials filed an arrest warrant for Do Kwon, but he is missing.

Do Kwon is now a fugitive in 195 countries after Seoul prosecutors placed him to Interpol's red list. Do Kwon hasn't commented since then. The red list allows any country's local authorities to apprehend Do Kwon.

Do Dwon and Terraform Labs were believed to have moved to Singapore days before the $40 billion wipeout, but Singapore authorities said he fled the country on September 17. Do Kwon tweeted that he wasn't on the run and cited privacy concerns.

Do Kwon was not on the red list at the time and said he wasn't "running," only to reply to his own tweet saying he hasn't jogged in a while and needed to trim calories.

Whether or not it makes sense to read too much into this, the reality is that Do Kwon is now on Interpol red list, despite the firmly asserts on twitter that he does absolutely nothing to hide.

UPDATE:

South Korean authorities are investigating alleged withdrawals of over $60 million U.S. and seeking to freeze these assets. Korean authorities believe a new wallet exchanged over 3000 BTC through OKX and Kucoin.

Do Kwon and the Luna Foundation Guard (of whom Do Kwon is a key member of) have declined all charges and dubbed this disinformation.

Singapore's Luna Foundation Guard (LFG) manages the Terra Ecosystem.

The Legal Situation

Multiple governments are searching for Do Kwon and five other Terraform Labs employees for financial markets legislation crimes.

South Korean authorities arrested a man suspected of tax fraud and Ponzi scheme.

The U.S. SEC is also examining Terraform Labs on how UST was advertised as a stablecoin. No legal precedent exists, so it's unclear what's illegal.

The future of Terraform Labs, Terra, and Terra 2 is unknown, and despite what Twitter shills say about LUNC, the company remains in limbo awaiting a decision that will determine its fate. This project isn't a wise investment.

Take a look at a YouTube channel making anything up to over $12k a month from making very simple videos.

And the best part? Its replicable by anyone. Basic videos can be generated for free without design abilities.

Join me as I deconstruct the channel to estimate how much they make, how they do it, and how you can too.

What Do They Do Exactly?

Happy Land posts memes with a simple caption they wrote. So, it's new. The videos are a slideshow of meme photos with stock music.

The site posts 12 times a day.

8-10-minute videos show 10 second images. Thus, each video needs 48-60 memes.

Memes are video titles (e.g. times a boyfriend was hilarious, back to school fails, funny restaurant signs).

Some stats about the channel:

• Founded on October 30, 2020

• 873 videos were added.

• 81.8k subscribers

• 67,244,196 views of the video

What Value Are They Adding?

Everyone can find free memes online. This channel collects similar memes into a single video so you don't have to scroll or click for more. It’s right there, you just keep watching and more will come.

By theming it, the audience is prepared for the video's content.

If you want hilarious animal memes or restaurant signs, choose the video and you'll get up to 60 memes without having to look for them. Genius!

How much money do they make?

According to www.socialblade.com, the channel earns $800-12.8k (image shown in my home currency of GBP).

That's a crazy estimate, but it highlights the unbelievable potential of a channel that presents memes.

This channel thrives on quantity, thus putting out videos is necessary to keep the flow continuing and capture its audience's attention.

How Are the Videos Made?

Straightforward. Memes are added to a presentation without editing (so you could make this in PowerPoint or Keynote).

Each slide should include a unique image and caption. Set 10 seconds per slide.

Add music and post the video.

Finding enough memes for the material and theming is difficult, but if you enjoy memes, this is a fun job.

This case study should have shown you that you don't need expensive software or design expertise to make entertaining videos. Why not try fresh, easy-to-do ideas and see where they lead?

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(f) Any Dispute must be filed within one year after the relevant claim arose; otherwise, the Dispute is permanently barred, meaning that neither you nor INTΞGRITY will be able to assert the claim.

(g) You have the right to opt-out of binding arbitration within 30 days of the date you initially accepted the terms of this section by sending an email to hello@int3grity.com. For the opt-out notification to be effective, it must include your full name and address and clearly explain your intent to opt out of binding arbitration. By declining binding arbitration, you consent to the resolution of Disputes in accordance with "Governing Law and Venue" below.

(h) If any portion of this section is found to be unenforceable or unlawful for any reason: (1) the unenforceable or unlawful provision shall be severed from these Terms; (2) the severance of the unenforceable or unlawful provision shall have no effect whatsoever on the remainder of this section or the parties' ability to compel arbitration of any remaining claims on an individual basis pursuant to this section; and (3) to the extent that any claims must therefore proceed on an individual basis, the parties agree to arbitrate those claims on an individual basis. In addition, if it is determined that any portion of this section prohibits an individual claim seeking public injunctive relief, that provision will be null and void to the extent that such relief may be sought outside of arbitration, and the balance of this section will be enforceable.

Statute and Location

These Terms and any dispute that may arise between you and INTΞGRITY are governed by California law, excluding its conflict of law provisions. Any issue between the parties that is not arbitrable or cannot be heard in small claims court will be determined by the state or federal courts of California and the United States, sitting in San Francisco, California.

Some nations have regulations that require agreements to be controlled by the consumer's country's laws. These statutes are not overridden by this paragraph.

Amendments

Periodically, we may make modifications to these Terms. If we make modifications, we will notify you by sending an email to the address connected with your account, providing an in-product message, or amending the date at the top of these Terms. Unless we specify otherwise in our notification, the modified Terms will take effect immediately, and your continued use of our Services after we issue such notice indicates your acceptance of the changes. If you do not accept the updated Terms, you must cease using our services.

Severability

If any section or portion of a provision of these Terms is determined to be unlawful, void, or unenforceable, that provision or part of the provision shall be deemed severable from these Terms and shall not affect the validity and enforceability of the other terms.

Miscellaneous INTΞGRITY’s omission to assert or enforce any right or term of these Terms is not a waiver of such right or provision. These Terms and the terms and policies specified in the Other Terms and Policies that May Apply to You Section constitute the complete agreement between the parties pertaining to the subject matter hereof and supersede all prior agreements, statements, and understandings between the parties. The section headings in these Terms are for convenience only and have no legal or contractual significance. The use of the word "including" shall be taken to mean "including without limitation." Unless otherwise specified, these Terms are intended solely for the benefit of the parties and are not intended to confer third-party beneficiary rights on any other person or entity. You consent to the use of electronic means for our communications and transactions.