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Boom! Data Science, Machine Learning, Artificial Intelligence news and learning resources. Our Data Science discussion group: @datascienceboomgroup For questions contact @andrew_avel
Syftr - an AI agent optimizer (open source) that helps you find the best AI agentic workflows for a given budget:
https://github.com/datarobot/syftr
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
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
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 🙌
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
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! 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
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
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
$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
Boom! What to read on the weekend, Issue #86
‘Trustworthy AI’ is a framework to help manage unique risk
https://bit.ly/39MLQud
StyleGAN for Evil: Trypophobia and Clockwork Oranging
https://bit.ly/349VK7Q
10 Awesome Data Manipulation and Wrangling Hacks, Tips and Tricks
https://bit.ly/3497WFP
Machine Learning: the Future of Farming
https://bit.ly/39H6awE
Coronavirus: We Need Better Data Hygiene
https://bit.ly/3aIqKhA
How to avoid astronomical AI computing costs
https://bit.ly/3aC6Ogp
Learn D3: Introduction
https://bit.ly/39FzhAJ
Fighting COVID-19 with Epidemiology: A Johns Hopkins Teach-Out
https://bit.ly/3dLWTXw
Introduction to KNN | K-nearest neighbor algorithm using Examples
https://bit.ly/3dQz157
Plastic Touch: AI in Healthcare
https://bit.ly/2V69HQe
DataRobot (AutoML AI Platform) is opening the access to all COVID-19 researchers. Sign up today to free!
https://bit.ly/2w53Rpy
How to Make Remote Work Effective for Data Science Teams
https://bit.ly/3dM5DNg
All AI`s are psychopaths
https://bit.ly/3dIyzpw
Interpretable Machine Learning. A Guide for Making Black Box Models Explainable.
https://bit.ly/2UADgu0
Leadership in a crisis: Responding to the coronavirus outbreak and future challenges
https://mck.co/2R1pe2c
Boom! Weekly selection from DSB. Issue #81
The TOP 10 most popular links of the week
1. Coronavirus Disease (COVID-19) – Research and Statistics, by Our World in Data
http://bit.ly/2WhUIEP
2. COVID-19: Implications for business
https://mck.co/2U7QjSn
3. Flatten the curve - COVID-19
http://bit.ly/2INdHz9
4. Pandas Cheat Sheet — Python for Data Science
http://bit.ly/2IMhVqH
5. Getting into Deep Learning? Here are 5 Things you Should Absolutely Know
http://bit.ly/2xHk8BB
6. Visualizing the History of Pandemics
http://bit.ly/3aVWOyi
7. Covid-19, your community, and you — a data science perspective
http://bit.ly/38SdgOz
8. Phishytics – Machine Learning for Detecting Phishing Websites
http://bit.ly/3aZaJ6U
9. What's so hard about PDF text extraction?
http://bit.ly/2Qy5Wl9
10. Deep Reinforcement Learning For Trading Applications
http://bit.ly/2IUxU61
AI could help with the next pandemic—but not with this one
http://bit.ly/2TPI8ei
Deep Reinforcement Learning For Trading Applications
http://bit.ly/2IUxU61
How much is too much?: The ethics of AI and data in the workplace
http://bit.ly/2TS7dFD
The Robots Are Coming
http://bit.ly/33isMlQ
A Beginner’s Guide to Random Forest Hyperparameter Tuning
http://bit.ly/39UYI1V
Getting into Deep Learning? Here are 5 Things you Should Absolutely Know
http://bit.ly/2xHk8BB
Phishytics – Machine Learning for Detecting Phishing Websites
http://bit.ly/3aZaJ6U
Flatten the curve - COVID-19
http://bit.ly/2INdHz9
Ten Research Challenge Areas in Data Science
http://bit.ly/2IQ0kyg
China tests AI that predicts earthquakes better than lousy humans
http://bit.ly/38W0xdM
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”.
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
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
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
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
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
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
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
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
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
Beyond coronavirus: The path to the next normal
https://mck.co/2ymnsCn
Generating music in the waveform domain
https://bit.ly/2wXsBR5
A blueprint for remote working: Lessons from China
https://mck.co/2JBXrkR
Support Vector Regression Tutorial for Machine Learning
https://bit.ly/2UDZ0VL
Responsible AI in times of pandemic
https://bit.ly/2x1dvtI
Boom! Monthly selection from DSB. Issue #23
The TOP 10 most popular links of the month (March 2020)
1. Coronavirus Disease (COVID-19) – Research and Statistics, by Our World in Data
http://bit.ly/2WhUIEP
2. Free Mathematics Courses for Data Science & Machine Learning
http://bit.ly/2Tctrl7
3. COVID-19: Implications for business
https://mck.co/2U7QjSn
4. Pandas Cheat Sheet — Python for Data Science
http://bit.ly/2IMhVqH
5. Flatten the curve - COVID-19
http://bit.ly/2INdHz9
6. 20 Ideas For 2020
http://bit.ly/39AgO9s
7. Visualizing the History of Pandemics
http://bit.ly/3aVWOyi
8. Covid-19, your community, and you — a data science perspective
http://bit.ly/38SdgOz
9. Mathematics for the adventurous self-learner
http://bit.ly/39eWHxq
10. Why your brain is not a computer
http://bit.ly/2IvdyAi
Boom! What to read on the weekend, Issue #85
Visualizing the History of Pandemics
http://bit.ly/3aVWOyi
Time to rethink the publication process in machine learning
http://bit.ly/33sdafG
Algorithms that run our lives are racist and sexist. Meet the women trying to fix them
http://bit.ly/2U758Ex
What Are My Photos Revealing About Me?
http://bit.ly/2U6duwc
Artificial Intelligence Will Do What We Ask. That’s a Problem.
http://bit.ly/2TRCiJj
The era of fake writing is upon us
http://bit.ly/3b1sHWq
Artificial Intelligence and the Manufacturing of Reality
http://bit.ly/2IQYw8d
A new management science for technology delivery
https://mck.co/39TYCI6
ChartIO: We made SQL visual - why and how
http://bit.ly/3d0JVER
The Remote Work Report by GitLab: The Future of Work is Remote
http://bit.ly/2WemJwX
All numbers are made up, some are useful
http://bit.ly/39R3KwE
COVID-19: Implications for business
https://mck.co/2U7QjSn
What's so hard about PDF text extraction?
http://bit.ly/2Qy5Wl9
How Bad Data is Affecting Your Organization’s Operational Efficiency
http://bit.ly/2IKYgHI
Google’s AI-powered smart glasses help the blind to see
http://bit.ly/39UTjYH
Fast and Easy Infinitely Wide Networks with Neural Tangents
http://bit.ly/2TZSWFu
Covid-19, your community, and you — a data science perspective
http://bit.ly/38SdgOz
Why we need more women to build real-world AI products, explained by science
http://bit.ly/38UrbUe
How HR Can Help Solve the Hiring Discrimination Crisis
http://bit.ly/39XBHvq
Data centers are the new oil
http://bit.ly/33iYCia