Boom! Weekly selection from DSB. Issue #82
The TOP 10 most popular links of the week

1. DataRobot (AutoML AI Platform) is opening the access to all COVID-19 researchers. Sign up today to free!
https://bit.ly/2w53Rpy

2. Beyond coronavirus: The path to the next normal
https://mck.co/2ymnsCn

3. Interpretable Machine Learning. A Guide for Making Black Box Models Explainable.
https://bit.ly/2UADgu0

4. A blueprint for remote working: Lessons from China
https://mck.co/2JBXrkR

5. All AI`s are psychopaths
https://bit.ly/3dIyzpw

6. 10 Awesome Data Manipulation and Wrangling Hacks, Tips and Tricks
https://bit.ly/3497WFP

7. Support Vector Regression Tutorial for Machine Learning
https://bit.ly/2UDZ0VL

8. Leadership in a crisis: Responding to the coronavirus outbreak and future challenges
https://mck.co/2R1pe2c

9. Introduction to KNN | K-nearest neighbor algorithm using Examples
https://bit.ly/3dQz157

10. How to Make Remote Work Effective for Data Science Teams
https://bit.ly/3dM5DNg

$69 Trillion of World Debt in One Infographic
https://bit.ly/39JauM6

Every Vaccine and Treatment in Development for COVID-19, So Far
https://bit.ly/2V0taSd

50 Must-Read Free Books For Every Data Scientist in 2020
https://bit.ly/2wTkLbl

COVID-19 Dashboards
https://bit.ly/2xOf52p

What is Federated Learning?
https://bit.ly/3bO6kUH

Should I Worry About... the philosophy behind AI?
https://bit.ly/3e0GbEb

To Beat COVID-19, Think Like a Fighter Pilot
https://bit.ly/2X90bhJ

Visualizing Neural Networks with the Grand Tour
https://bit.ly/2UH3AT8

The Hardest Hit Companies of the COVID-19 Downturn: The ‘BEACH’ Stocks
https://bit.ly/2V1yk07

What is Multicollinearity? Here’s Everything You Need to Know
https://bit.ly/2X8g2Nr

Text Summarization Papers
https://bit.ly/3aJKYrs

Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve”
https://wapo.st/2XbkGdt

Agent57: Outperforming the human Atari benchmark
https://bit.ly/2V0tUGZ

Outbreak
https://bit.ly/2xQRjm8

What you need to know about product management for AI
https://bit.ly/2xLcPc6

When to assume neural networks can solve a problem
https://bit.ly/2x2R3AC

Why It’s So Freaking Hard To Make A Good COVID-19 Model
https://53eig.ht/2Rcwh8n

Using Graphs to Identify Social Media Influencers
https://bit.ly/2Xg5EU9

The Math Behind Social Distancing
https://bit.ly/2V5kytB

My First Year as a Data Scientist
https://bit.ly/2UZwz3L

Feature Scaling for Machine Learning: Understanding the Difference Between Normalization vs. Standardization
https://bit.ly/2UG1TWi

Social Media Posts and Online Searches Hold Vital Clues about Pandemic Spread
https://bit.ly/2ULI3sR

Can you Lie to your Deep Learning Model?
https://bit.ly/39Hqdv5

An Analyst’s Perspective on COVID-19’s Economic Impact on Businesses
https://bit.ly/348ZHJQ

Exploratory Data Analysis for Text Data
https://bit.ly/2V6Jsc6

Boom! What to read on the weekend, Issue #87

Google uses AI to enhance video call audio
https://bbc.in/3dQUdrI

A Closer Look at Location Data: Privacy and Pandemics
https://bit.ly/3bQneBX

Artificial intelligence decodes the facial expressions of mice
https://go.nature.com/2UFszGC

New Artificial Intelligence Priorities in the COVID-19 Era
https://bit.ly/3dT0Uti

Imagining a new interface: Hands-free communication without saying a word
https://bit.ly/2yAcxFs

Keeping Data Inclusivity Without Diluting your Results
https://bit.ly/2RrDJgj

AI Advantages and Challenges in the Coronavirus Era
https://bit.ly/3aIzsg1

GroupBy in Pandas: Your Guide to Summarizing and Aggregating Data in Python
https://bit.ly/2xRFdcp

Franken-algorithms: the deadly consequences of unpredictable code
https://bit.ly/2R9H2IC

Mathematics as a Team Sport
https://bit.ly/2xLdQAW

Boom! Weekly selection from DSB. Issue #83
The TOP 10 most popular links of the week

1. 50 Must-Read Free Books For Every Data Scientist in 2020
https://bit.ly/2wTkLbl

2. $69 Trillion of World Debt in One Infographic
https://bit.ly/39JauM6

3. COVID-19 Dashboards
https://bit.ly/2xOf52p

4. Text Summarization Papers
https://bit.ly/3aJKYrs

5. Every Vaccine and Treatment in Development for COVID-19, So Far
https://bit.ly/2V0taSd

6. When to assume neural networks can solve a problem
https://bit.ly/2x2R3AC

7. What is Federated Learning?
https://bit.ly/3bO6kUH

8. My First Year as a Data Scientist
https://bit.ly/2UZwz3L

9. Feature Scaling for Machine Learning: Understanding the Difference Between Normalization vs. Standardization
https://bit.ly/2UG1TWi

10. Exploratory Data Analysis for Text Data
https://bit.ly/2V6Jsc6

Data Science: Reality Doesn't Meet Expectations
https://bit.ly/2VpDxPP

Monitoring Machine Learning Models in Production
https://bit.ly/2JXTEyC

Time Series Forecasting Best Practices & Examples
https://bit.ly/2K1g6GU

3 Reasons Why We Are Far From Achieving Artificial General Intelligence
https://bit.ly/34uisYp

Why I’m not making COVID19 visualizations, and why you (probably) shouldn’t either
https://bit.ly/3cakxeD

The Seven Sins of Data Prep
https://bit.ly/2RvqgEd

After coronavirus, AI could be central to our new normal
https://bit.ly/2VlLlC6

Towards understanding glasses with graph neural networks
https://bit.ly/2XwGvVo

Scientists have created a new type of robot that is literally alive
https://bit.ly/2XwGXTA

​​​​28 Jupyter Notebook Tips, Tricks, and Shortcuts
https://bit.ly/2Vi4ncs

Boom! Monthly selection from DSB. Issue #24
The TOP 10 most popular links of the month (April 2020)

1. 50 Must-Read Free Books For Every Data Scientist in 2020
https://bit.ly/2wTkLbl

2. $69 Trillion of World Debt in One Infographic
https://bit.ly/39JauM6

3. COVID-19 Dashboards
https://bit.ly/2xOf52p

4. 28 Jupyter Notebook Tips, Tricks, and Shortcuts
https://bit.ly/2Vi4ncs

5. The Seven Sins of Data Prep
https://bit.ly/2RvqgEd

6. Time Series Forecasting Best Practices & Examples
https://bit.ly/2K1g6GU

7. DataRobot (AutoML AI Platform) is opening the access to all COVID-19 researchers.
https://bit.ly/2w53Rpy

8. Beyond coronavirus: The path to the next normal
https://mck.co/2ymnsCn

9. My First Year as a Data Scientist
https://bit.ly/2UZwz3L

10. 10 Awesome Data Manipulation and Wrangling Hacks, Tips and Tricks
https://bit.ly/3497WFP

Boston Dynamics is open-sourcing its robot tech to help hospitals fight coronavirus
https://bit.ly/2KXoXtK

A state-of-the-art open source chatbot from Facebook
https://bit.ly/3b1jwEI

Why We Need DevOps for ML Data
https://bit.ly/3fbobY6

Why You Should Ignore All That Coronavirus-Inspired Productivity Pressure
https://bit.ly/2z39iGI

Statistics for Data Science: What is Normal Distribution?
https://bit.ly/3b18EXo

Jukebox - a neural net that generates music.
https://bit.ly/3db0MEh

The Unprecedented Line Charts of COVID-19
https://bit.ly/2zeHD5B

Google Drive is production
https://bit.ly/3c6zkaH

PyBoy - Game Boy emulator written in Python to train AI systems
https://bit.ly/3dbrkFm

Intro to Automated Question Answering
https://bit.ly/35trkOC

Hey guys! Hope you are all great 🙌

ProductStar Global holds free weekly online meetup this Sunday (10/05) for anyone who is interested in product management! 👌

Manasa GN, Product Manager at Shell will talk about "Feature table building which helps understand different types of Product Managers in the industry".😎

They say ideas are 'a dime a dozen' but where do good ideas come from? Do they come from observation, personal experience, or research?
Manasa will explore these questions in this discussion. 🚀
Key points:
🔸 Understand the different types of Product Managers in the industry
🔸 How to use the EMUC model to look for good ideas.
🔸 Learn how to build Feature tables for Product Managers

Join the webinar by the following link https://productstar.org/productwebinar
🗓 May 10th (Sunday)
⏰ 13.00 GMT, 18.30 IST, 20.00 Jakarta

It’s going to be really interesting, so Invite your friends and share the information with your colleagues 🙌

Online Seminar on Mathematical Foundations of Data Science
https://bit.ly/3bikw7x

7 Reasons To Not Hire a Data Scientist
https://bit.ly/2YBa48y

Don’t Fear the Robot
https://bit.ly/2WIGhrV

CNN Explainer. Learn Convolutional Neural Network (CNN) in your browser!
https://bit.ly/35LUqZu

My First Year as a Freelance AI Engineer
https://bit.ly/3clyNBV

Using Neural Networks to Find Answers in Tables
https://bit.ly/2WLpHHQ

The Art of Storytelling in Analytics and Data Science | How to Create Data Stories?
https://bit.ly/3dHfBPs

AI and Efficiency
https://bit.ly/2Lq2wO0

The Nooscope Manifested. AI as Instrument of Knowledge Extractivism
https://bit.ly/2WNmcRw

Don’t Regulate Artificial Intelligence: Starve It
https://bit.ly/2WNNQ0G

Technologication Business Conference

On July 15, at the Technologication online conference, we will speak with Amazon Web Services, Booking, Microsoft and Genesis Investment about new approaches to business transformation. We are waiting for an intensive 6 hours of cases of companies that have survived more than one crisis, and many times "re-assembled" their business.

👉 What are we going to talk about?
• “Amazon's Culture of Innovation,” - Attila Lengyel, Digital Innovation Senior BDM at Amazon Web Services EMEA.
• "The 7 powers of Machine Learning" - Lucas Bernardi, Principal Data Scientist at Booking.com.
• "Turning Crisis Into Opportunities In Startups and VC" - Elena Mazhuha, Investment Manager at Genesis Investments.
• "Technology: business in a new way", - Grigory Bakunov, VP of Technology at Parimatch.
• “How Microsoft is Putting Responsible AI into Practice” - Xiaopeng Li, Data & AI Business Lead at Microsoft.

👉 Who will be interested?
Entrepreneurs, IT departments, business development and marketing departments.

When: July 15, 15:00 to 21:00 EEST
Where: online
Participation is free by prior registration: https://bit.ly/Technologication

My name is Andriy Velihotskyi and I am Ukrainian. I am the author of DSB.

I am proud to live in Ukraine, however, at the moment my country is going through the War with Russian Federation.

On 24 February 2022, Russia launched a large-scale military invasion of Ukraine. While our army is fighting strongly against one of the biggest countries in the world, we need help.
This is my call to action. We must stop the war in Ukraine!

You can help in numerous ways:
1. Donate money for our Army needs:
- https://uahelp.monobank.ua
- https://bank.gov.ua/en/news/all/natsionalniy-bank-vidkriv-spetsrahunok-dlya-zboru-koshtiv-na-potrebi-armiyi
- https://putler.io
2. Join a protest in your city against Russian aggression
3. Host Ukrainians and help locally
4. Check more details specific to your country here:
- https://supportukrainenow.org/
- https://ukraine.ua/news/stand-with-ukraine/

We really need your support! Glory to Ukraine!
#supportukraine #standwithukraine

AI HOUSE launches a new educational project AI for Ukraine!

AI for Ukraine is a series of workshops and lectures held by international artificial intelligence experts to support the development of Ukraine’s tech community during the war.

Yoshua Bengio (Mila/U. Montreal), Alex J. Smola (Amazon Web), Sebastian Bubeck (Microsoft), Gaël Varoquaux (INRIA), Alexander Rush (Hugging Face) and many other well-known specialists in machine learning have joined the initiative.

AI HOUSE united the international AI community to support Ukrainian people during the war and provide Ukrainian talents with access to quality education in artificial intelligence and machine learning.

“AI for Ukraine” is a non-commercial educational initiative, which aims to:

— Provide Ukrainian talents with access to quality education in artificial intelligence
— Raise funds to support the Ukrainian people
— Involve global AI leaders in the development of the Ukrainian AI community
— Strengthen ties and expand the network of Ukrainian and international specialists

The first lecture will be held by Yoshua Bengio on August 17th.
Don’t miss it and register now at https://aiforukraine.aihouse.club/

Upon registration, participants will be required to make a deposit of any amount ($1 minimum) to receive full access to all upcoming lectures and workshops. All collected funds will be donated to Ukraine’s largest charity fund “Come back alive”.