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"Think Python" by Allen Downey.
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OpenAI CEO, Sam Altman, testified before Congress yesterday for 4 hours.
Don't have the time to watch it all?
We've collected the highlights that are already resonating with people 🧵
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TimeGPT is the first foundation model specifically designed for time series analysis.
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CS106A - Programming Methodology course
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38 lectures
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Linear algebra course materials
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1) Lecture videos and slides
2) Homeworks
3) Exams and solutions
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Introduction to computer science and programming course materials
@MIT
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1. Lecture videos
2. Assignments
3. Exams
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CS109A Data Science course materials
@Harvard
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1. Lecture notes
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A free Artificial Intelligence for Beginners course by
@Microsoft
.
▪️ 12 weeks
▪️ 24 lessons
It introduces learners to the world of AI.
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CS 224: Advanced Algorithms course
@Harvard
is open for everyone!
Materials:
- Lecture slides and videos
- Assignments
For more:
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Machine learning is famous for its open resources.
We collected 3 free courses about ML:
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@MIT
▪️ Mathematics for Computer Science,
@MIT
▪️ Practical Deep Learning,
@fastdotai
🧵
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A free book for you!
Learn:
1. NumPy & Pandas
2. Matplotlib: data visualizations
3. Scikit-Learn: efficient & clean implementations of ML algorithms
Read the open "Python Data Science Handbook: Essential Tools for Working with Data":
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Free book on Statistics!
Introduction to Modern Statistics.
Read here:
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Mathematics of Big Data and Machine Learning course materials by
@MIT
are free and open for everyone!
Find:
1. Lecture notes
2. Lecture videos
3. Slides
Learn here:
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CS 224: Advanced Algorithms course
@Harvard
is open for everyone!
Materials:
- Lecture slides and videos
- Assignments
For more:
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Linear Algebra course by
@MIT
is free and open for everyone!
Find:
1. Videos and lecture notes
2. Assignments: problem sets with solutions
3. Exams and solutions
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Microsoft presented Azure ChatGPT.
The code is open-sourced under MIT Licence.
Benefits:
1. Privacy: Fully isolated from data operated by OpenAI.
2. Control: Network traffic can be fully isolated to your network
3. Plug-n-play: Add your internal data sources or use plug-ins
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A free book for you!
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1. NumPy & Pandas
2. Matplotlib: data visualizations
3. Scikit-Learn: efficient & clean ML algorithms
Read the open "Python Data Science Handbook: Essential Tools for Working with Data":
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"NLP with Deep Learning" by
@stanfordnlp
is free and open!
Find links on:
- lecture slides
- lecture videos
- notes
- codes
- suggested readings
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5 latest open-source LLMs (save the list)
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A free book for you!
Fundamentals of Data Visualization by Claus O. Wilke
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"Introduction to Probability for Data Science" by Stanley H. Chan.
Read here:
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"NLP with Deep Learning" by
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is free and open!
Find links on:
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- lecture videos
- notes
- codes
- suggested readings
All is here⬇️
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Happy Holidays, friends!🥳
We've made a recap of the most popular courses for you.
1. Deep Learning by
@ylecun
,
@alfcnz
2. Linear Algebra
@MIT
3. Deep Learning for NLP
@DeepMind
,
@CompSciOxford
Find links in the thread!
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Download your copy of Understanding Machine Learning: From Theory to Algorithms book by Shai Shalev-Shwartz and Shai Ben-David.
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🔗
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Check out a free edition of Think Bayes by Allen Downey.
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3. Code is written in NumPy, SciPy, and Pandas
Find it here for free:
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Mathematics of Big Data and Machine Learning course materials by
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are free and open for everyone!
Find:
1. Lecture notes
2. Lecture videos
3. Slides
Learn here:
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A free book for you!
Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong.
Learn Maths for ML here:
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Linear Algebra course by
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2. Assignments: problem sets with solutions
3. Exams and solutions
Learn the basics here:
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8 free ML courses -- our favorites:
1. Deep Learning
@nyuniversity
2. NLP with Deep Learning
@Stanford
3. Learning From Data
@Caltech
4. Full-stack production deep learning (DL)
@UCBerkeley
5. Linear Algebra Review
@CarnegieMellon
Check the rest here:
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A free book for you!
Learn:
1. NumPy & Pandas
2. Matplotlib: data visualizations
3. Scikit-Learn: efficient implementations of ML algorithms
Read the open "Python Data Science Handbook: Essential Tools for Working with Data":
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"Deep Learning for Natural Language Processing" course lectures are open for everyone!
It's an advanced course from
@CompSciOxford
and
@DeepMind
.
All lecture materials, recordings, and practicals:
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A free book for you!
Learn:
1. NumPy & Pandas
2. Matplotlib: data visualizations
3. Scikit-Learn: efficient & clean implementations of ML algorithms
Read the open "Python Data Science Handbook: Essential Tools for Working with Data":
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A free book for you!
Hands-On Data Visualization by Hands-On Data Visualization has an open version.
It takes you step-by-step through
1. tutorials
2. real-world examples
3. online resources
Read here:
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3 free MLOps courses you should know about:
▪️ MLOps Course,
@GokuMohandas
▪️ CS 329S: Machine Learning Systems Design
@Stanford
▪️ MLOps Zoomcamp
@Al_Grigor
🧵
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Machine learning is famous for its open resources.
We collected 3 free courses about ML:
▪️ Introduction to Machine Learning,
@MIT
▪️ Mathematics for Computer Science,
@MIT
▪️ Practical Deep Learning,
@fastdotai
🧵
3
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564
Yann
@ylecun
LeCun’s Deep Learning Course Is Now Free & Fully Online at
@NYUDataScience
#AI
#DeepLearning
#MachineLanguage
#MachineLearning
#Education
#thesequence
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"NLP with Deep Learning" by
@stanfordnlp
is free and open!
Find links on:
1. lecture slides & videos
2. notes
3. codes
4. suggested readings
All is here⬇️
2
152
559
"Deep Learning for Natural Language Processing" course lectures are open for everyone!
It's an advanced course from
@CompSciOxford
and
@DeepMind
.
All lecture materials, recordings, and practicals:
0
149
550
Recently, PyTorch introduced mm, a 3D matrix multiplication (matmul) visualizer.
This tool is interactive, runs in the browser or notebook iframes, and features shareable links.
You can visualize:
• Matrix multiplications
• Attention heads
• LORA
Some examples:
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A free book for you!
"Foundations of Data Science" by Avrim Blum, John Hopcroft, and Ravindran Kannan.
It provides an introduction to the mathematical and algorithmic foundations of data science.
Find it here:
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145
550
A free book for you!
"Foundations of Data Science" by Avrim Blum, John Hopcroft, and Ravindran Kannan.
It provides an introduction to the mathematical and algorithmic foundations of data science.
Find it here:
4
136
540
"NLP with Deep Learning" by
@stanfordnlp
is free and open!
Find links on:
1. lecture slides & videos
2. notes
3. codes
4. suggested readings
All is here⬇️
0
156
536
Mathematics for Computer Science course
@MIT
is open for everyone!
1. Definitions, proofs, sets, functions, relations
2. Discrete structures: graphs, state machines, modular arithmetic, counting
3. Discrete probability theory
1
146
530
A free book for you!
Learn:
1. NumPy & Pandas
2. Matplotlib: data visualizations
3. Scikit-Learn: efficient & clean ML algorithms
Read the open "Python Data Science Handbook: Essential Tools for Working with Data":
3
139
518
Python for Data Science, AI & Development is a free course by
@IBM
.
It will take you from 0 to programming in Python.
It consists of 4 weeks:
1. Basics
2. Data Structures
3. Programming Fundamentals
4. Working with Data
Learn here:
7
156
527
A free book for you!
Hands-On Data Visualization,
@HandsOnDataViz
has an open version.
It takes you step-by-step through
1. tutorials
2. real-world examples
3. online resources
Read here:
4
138
530
8 free courses to master large language models:
- Cohere LLM University
- Hugging Face NLP course
- DeepLearning AI courses
- Weights & Biases course
- Introduction to LLMs course by Google Cloud
...
🧵
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133
523
Running LLMs on consumer GPUs.
Notes, tutorials, and examples in one thread 🧵
7
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515
Microsoft, MIT, and Google collaborated to transform the entire Project Gutenberg Collection into audiobooks.
The library now boasts over 800 audiobooks!
Utilizing advanced AI models for text-to-audio conversion, the team achieved exceptional quality of voice acting.
Large-Scale Automatic Audiobook Creation
paper page:
An audiobook can dramatically improve a work of literature's accessibility and improve reader engagement. However, audiobooks can take hundreds of hours of human effort to create, edit, and publish. In
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5
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A repo containing the best AI courses/resources.
The courses are ranked by difficulty, so there's something for everyone!
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A free book for you!
Machine Learning Simplified. A Gentle Introduction to Supervised Learning
Read here for free:
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145
490
Chain-of-thought Lineage:
▪️ Chain-of-thought prompting
▪️ Self-consistency
▪️ Zero-Shot Chain-of-Thought
▪️ Automatic-Chain-of-Thought
▪️ Program-of-Thoughts Prompting
▪️ Multimodal Chain-of-Thought Reasoning
▪️ Tree-of-Thoughts
▪️ Graph-of-Thoughts
▪️ Algorithm-of-Thoughts
▪️
3
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Linear Algebra course by
@MIT
is free and open for everyone!
Find:
1. Videos and lecture notes
2. Assignments: problem sets with solutions
3. Exams and solutions
Learn the basics:
0
122
482
ML Research of this week:
1.
@MetaAI
Data2vec
2.
@GoogleAI
MoE Task Routing
3.
@MSFTResearch
DeepSpeed and MoE
4.
@GoogleAI
StylEx – Visual Interpretability of Classifiers
Find details here:
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If you're in ML, chances are you completed the
@AndrewYNg
ML specialization.
But what if we told you there's an incredible resource to help you refresh your knowledge? Or even pass the course from scratch?
Notes and implementations of algorithms
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Here is an open version of "Deep Learning with
@PyTorch
".
Read and download it here, for free:
5
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Check out the open edition of Think Bayes by
@AllenDowney
.
1. This book uses Python code instead of math!
2. There’s a Jupyter notebook for every chapter
3. Code is written in NumPy, SciPy, and Pandas
Find it here for free:
1
115
456
"NLP with Deep Learning" by
@stanfordnlp
is free and open!
Find links on:
1. lecture slides & videos
2. notes
3. codes
4. suggested readings
All is here⬇️
2
127
447
If you're in ML, chances are you completed the
@AndrewYNg
ML specialization.
But what if we told you there's an incredible resource to help you refresh your knowledge? Or even pass the course from scratch?
Notes and implementations of algorithms
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123
449
We recommend you a free Learning From Data course with 7M views
@Caltech
.
It covers: basic ML theory, algorithms, and applications
Find the materials:
1. Lectures
2. Homework materials & solution keys.
Learn here:
3
127
439
Free book on Statistics!
Introduction to Modern Statistics covers:
1. Exploratory data analysis
2. Regression modeling
3. Statistical inference
Read here:
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120
438
A free book for you!
"Think Python" by Allen Downey.
Read here:
16
121
427
"NLP with Deep Learning" by
@stanfordnlp
is free and open!
Find links on:
- lecture slides
- lecture videos
- notes
- codes
- suggested readings
All is here⬇️
9
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We recommend you "Learning From Data" course (
@telecourse
)
@Caltech
.
It covers: basic ML theory, algorithms, and applications
Find the materials of the course with 7M views:
1. Lectures
2. Homework materials
There is a solution key for each homework!
1
97
431
A free book for you!
"The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, Jerome Friedman.
Read here:
3
103
423
A FREE tutorial on diffusion models and flow matching for ML!
Created by
@Apple
, Mila and
@UMontreal
, this tutorial simplifies the math but ensures precision for deriving correct algorithms.
Audience: beginners in diffusion with a technical background, such as advanced
1
120
435
8 Free Courses to Master Large Language Models:
1.
@cohere
LLM University
2.
@huggingface
NLP course
3.
@databricks
courses
and more!
🧵
4
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429
Introduction to Machine Learning
@MIT
is available to anyone!
1. Understand the formulation of ML problems
2. Learn how to perform supervised and reinforcement learning, with images and temporal sequences
Learn here:
2
123
422
Math background for ML lecture videos
@CarnegieMellon
are available for everyone!
The course provides the necessary mathematical background for further study in ML.
Find videos here:
Happy holidays, friends!☺
1
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Our favorite open ML courses!
Topics?
1. Deep Learning by
@ylecun
2. NLP with Deep Learning by
@stanfordnlp
3. Deep Learning for NLP by
@CompSciOxford
and
@DeepMind
Here they are⬇️
6
92
414
"Deep Learning for Natural Language Processing" course lectures are open for everyone!
It's an advanced course from
@CompSciOxford
,
@DeepMind
taught by Phil Blunsom.
All lecture materials, recordings, and practicals:
3
117
417
Introduction to Deep Learning course by
@TU_Muenchen
is free and open for everyone!
Find course materials by
@MattNiessner
:
1) Lecture slides
2) Recordings
3) Tutorials and exercises
Discover it here:
2
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416
8 free ML courses -- our favorites. We've put them all in one place.
Get the full list with links here:
All courses are online and free.
2
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405
3 free books, the most popular ones!
1. Fundamentals of Data Visualization
2. Hands-On Data Visualization
3. Reinforcement Learning: An Introduction
Share this post with your friends to spread the word!
1/2
5
122
397
Autonomous AI is a new trend.
2 repos were highly talked about everywhere
▪️ Auto-GPT
@SigGravitas
▪️ BabyAGI
@yoheinakajima
Original tweets, experiments, and opinions 🧵
8
88
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A free book on Computer Vision!
"Computer Vision: Algorithms and Applications" by Richard Szeliski.
Read it on the author's website:
6
117
393
Prepare to be amazed! 🤯 This library contains a vast collection of algorithms implemented in Python.
With an astonishing 171k stars on GitHub, it covers:
- Arithmetic Analysis
- Blockchain
- Data Structures
And much, much more.
1
79
398
Introduction to Machine Learning course materials from
@CarnegieMellon
are available to everyone!
▪️ Lecture slides and useful links
▪️ Handouts
▪️ Homework assignments
🔗
3
106
387
If you're in ML, chances are you completed the
@AndrewYNg
ML specialization.
But what if we told you there's an incredible resource to help you refresh your knowledge? Or even pass the course from scratch?
Notes and implementations of algorithms
3
98
387
Meet 🦍Gorilla: LLM connected with massive APIs
With Gorilla, you can effortlessly navigate over 1,600 API calls with minimal error!
It surpasses the performance of GPT-4 when it comes to making API invocations.
What's even better? You are free to use Gorilla for commercial
8
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384
A free book for you! The first book on AutoML!
AutoML: Methods, Systems, Challenges.
Read here:
1
90
381
A free book for you!
The Data Science Handbook is a compilation of in-depth interviews with 25 data scientists.
The book was created by
@wzchen
, Carl Shan, Henry Wang, Max Song.
You can pay for ebook or download it for free:
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