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Jean de Nyandwi @ ✈️🌁COLM 26

@Jeande_d50k followers

CS PhD, MS @CarnegieMellon • NLP, Data, Evals, Agents Blog ML Frontiers

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1Jun 5, '23Statistics 110: Probability - Harvard Inarguably, one of the classic/world's best probability courses on the web!!39.6×737k5.8k1.2k5.9k
2Dec 17, '22Applied Machine Learning - Cornell CS5785 "Starting from the very basics, covering all of the most important ML algorithms and how to apply them in practice. Executable Jupyter not16.3×304k3.2k8032.2k
3Jun 14, '23Understanding Deep Learning - BOOK Wow, this is such a great deep learning textbook. Covers almost all fundamental neural network techniques and algorithms. The content outline is 14.7×274k1.7k4061.9k
4Jul 8, '23Code Interpreter by OpenAI is truly a game changer. It's an analyst/assistant on your fingertip, who have general knowledge about the world(such as mathematics, stats, economics, e12.7×235k750107592
5Aug 23, '23Natural Language Processing - UT Austin A concise series of NLP lectures from UT Austin. Covers a vector of topics from basics of machine learning, NLP fundamentals, models(BERT, B12.4×231k9572211.4k
6Feb 4, '23Stanford CS 324 - Large Language Models - Lecture Notes 2022 A handy notes on various topics and techniques related to large language models. Notes are structured really well and t12.2×226k1.9k4181.4k
7Apr 23, '23The Little Book of Deep Learning A very concise/brief book on deep learning. Covers almost any topic you'd want to know today from foundations, efficient computation, model archite11.9×221k2.1k4941.6k
8Jan 7, '23MIT Introduction to Deep Learning - 2023 Starting soon! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures, a11.8×219k2.4k5631.1k
9Oct 15, '23The Little Book of Deep Learning, François Fleuret, University of Geneva Arguably one of the most concise deep learning books on the web. Covers a range of topics from fundamentals11.4×212k1.4k2931.9k
10Jan 2, '23Deep Learning with PyTorch - University of Amsterdam(UvA) A fantastic series of tutorials covering a wide array of topics from PyTorch basics, basics of neural nets, architectures(11×205k2k5291.2k
11Mar 31, '23Applied Machine Learning (Cornell CS5785) "Starting from the very basics, covering all of the most important ML algorithms and how to apply them in practice. Executable Jupyter not10.4×193k1.7k4361.6k
12Apr 2, '23Introduction to Deep Learning, Carnegie Mellon 2022-23 A nice set of lectures that covers the foundation of deep learning. Goes all the way from the history of DL, neural network t9.6×178k1.5k3371.3k
13May 27, '23Everything You Always Wanted To Know About Mathematics The title says it all: A handy guide on almost everything you would want to know about mathematics. Free copy:9.4×175k1.3k2411k
14Jan 4, '23Machine Learning Engineering for Production (MLOps) - DeepLearningAI Building models is one thing. Making them useful is another thing. The first course of the MLOps specialization8.8×164k2.2k5171.1k
15Feb 11, '23Deep Learning and Computational Physics - Lecture Notes, University of South California Great & concise notes on various fundamental topics in deep learning. The notes got a ni8.5×159k1.6k337913
16Dec 23, '22Stanford CS330: Deep Multi-Task and Meta Learning 2021 CS330 is a free course that covers a number of topics related to multi-task and meta-learning such as transfer learning, life8.0×149k1.7k360710
17Apr 18, '23Pen and Paper Exercises in Machine Learning A handy collection of pen-and-paper exercises in machine learning. Covers foundational topics related to machine learning such as linear7.9×148k739181782
18Jan 6, '23[NEW] Machine Learning Specialization - Andrew Ng ML specialization is the revamped edition of the former Stanford machine learning, one of the famous and earliest AI courses. Mate7.8×146k1.7k393786
19Dec 31, '22Intro to Machine - University of Waterloo A really nice machine learning introductory course that covers a number of topics from classical learning algorithms to modern deep learni7.7×144k1.3k349759
20Apr 1, '23Advanced Natural Language Processing - Class Notes, University of Southern California Great and concise notes on various techniques and algorithms in natural language processing. N7.7×143k1k226809
21Aug 19, '23[Lecture notes] Stanford CS324 - Large Language Models Excellent notes on various topics related to large language models: fundamentals of language models, capabilities of LLMs, da7.5×140k9732681.1k
22Jan 26, '23AI Research Experience - Harvard CS197 AI Research course and book that teaches how to do cutting-edge research, research workflows, and using tools commonly used in AI research(li7.4×138k1.3k338732
23Nov 11, '24Applied Machine Learning - Cornell CS5785 "Starting from the very basics, covering all of the most important ML algorithms and how to apply them in practice. Executable Jupyter not6.9×129k2.2k4113.3k
24May 2, '22You might not believe it, but the following 6 machine learning books are fully free: - Deep Learning - Dive into Deep Learning - Machine Learning Engineering - Python Data Science 6.8×04.2k1.2k2.6k
25Jan 12, '23Reproducible Data Analysis in Jupyter - Jake Vanderplas Nice videos on some best practices when doing data analysis in Jupyter notebooks. Covers topics like working with data &6.7×124k1k280578
26Jul 31, '23This Cookbook by OpenAI is an excellent resource that contains code and guides for performing common tasks with OpenAI API, ChatGPT, and their other services. Some examples of guid6.4×120k835207972
27Jun 29, '24Linear Algebra for Computer Vision, Robotics, and Machine Learning6.4×118k1.6k3361.9k
28Sep 30, '23TinyML and Efficient Deep Learning Computing, MIT 2023 A course that covers efficient AI techniques used for deploying deep learning models on resource-constrained devices. The top6.3×118k1k248982
29Jan 14, '23Multimodal Deep Learning - New Book Multimodal learning(MML) is one of the hottest areas in AI research these days. MML has advanced a lot in recent times. We've seen models that g6.1×114k925234342
30Jul 4, '24Vector Calculus6.1×113k9521431.1k
31Sep 2, '23Vision of Linear Algebra, Gilbert Strang at MIT Really like those new mini-lectures on linear algebra. Gilbert Strang decomposing complex topics into chunks of matrix/vector transf6.0×111k994209796
32Jan 17, '23Introduction to Deep Learning - Carnegie Mellon 2022 Intro to DL is one of the respected courses at CMU. The course covers a wide range of topics related to DL, from foundations, n5.9×111k1.2k300569
33Dec 26, '22Advanced Machine Learning for Remote Sensing - University of Bonn Machine learning is an incredible technology but its value is closed tied to where it is applied. Remote sensing i5.9×109k930226462
34Oct 23, '22Applied Machine Learning (Cornell CS5785) "Starting from the very basics, covering all of the most important ML algorithms and how to apply them in practice. Executable Jupyter not5.8×03k6402.9k
35Aug 14, '23Stanford CS229: Machine Learning, Spring 2022 CS229 is one of the best machine learning courses that provides a broad introduction to machine learning. The 2022 version was made av5.6×104k9181951k
36Jul 11, '23Long-awaited...An Introduction to Statistical Learning, one of the classical machine learning books is finally available in Python. Same contents as existing R version but now with5.4×100k729197642
37Apr 7, '23MIT Intro to Deep Learning - 2023 Lectures are Live MIT Intro to Deep Learning is one of few concise deep learning courses on the web. The course quickly takes you to the foundatio5.3×98k855238505
38Sep 23, '23[New Lectures] Stanford CS224N: Natural Language Processing with Deep Learning Stanford NLP course is arguably one of the best Deep NLP courses on the web. The new lectures from 205.2×98k760226800
39Dec 20, '22Advanced Natural Language Processing - CMU 2022 Advanced NLP is one of the best & modern NLP courses that cover fundamental tasks and recent advances in NLP. The Fall '22 mater5.1×96k1.1k281582
40Jan 9, '23A Succinct Summary of Reinforcement Learning A brief(but comprehensive) summary of reinforcement learning. This is an excellent resource for anyone who wants to brush up on basic t4.8×90k791129433
41Oct 10, '22Statistics 110: Probability - Harvard Inarguably, one of the classic probability courses on the web!!4.7×02.8k5102.2k
42Mar 5, '23Deep Learning , University of Liège A nice collection of lectures on various deep learning topics such as deep learning foundations, training neural networks, architectures, etc...4.7×87k1k244542
43Dec 16, '22The Principles of Deep Learning Theory A great textbook for understanding the mechanics of neural networks. The book draft is free!! Website: PDF copy via ArXiv:4.6×85k1.1k255394
44Jan 24, '23Understanding Deep Learning A great textbook that covers foundations of deep learning, techniques for training neural networks, and modern neural network architectures(CNNs, Transf4.5×83k895230451
45Dec 31, '24If you're into generative AI and LLMs and would like to understand the underlying tech/tools/models, get this book. Go into debt if you have to.4.4×83k982100958
46Jan 10, '23Neural Networks: Zero to Hero - Andrej Karpathy A growing series of lectures on various fundamental neural network techniques and architectures. From backward prop, MLPs, language 4.2×78k867196405
47Mar 6, '25RL won Turing Award to day. Richard Sutton and Andrew Barto. For anyone getting the excitement to dive in RL after Turing Award and reasoning models, here is a copy of all-time RL 4.2×77k1.1k136950
48Jul 14, '25Reinforcement Learning of Large Language Models, Spring 2025(UCLA) Great set of new lectures on reinforcement learning of LLMs. Covers a wide range of topics related to RLxLLMs suc4.1×76k1.3k2261.7k
49Oct 8, '24Deep Learning and Computational Physics - Lecture Notes, University of South California Great and concise notes on various fundamental topics in deep learning, drawing connections 4.0×75k1.1k1861.2k
50Jan 23, '23Everything is Connected: Graph Neural Networks Graphs Neural Networks(GNNs) are increasingly showing potential in modeling graphs datasets. @PetarV_93 just published a survey paper3.7×70k718181272
51Sep 26, '21Releasing a complete machine learning package containing over 30 end to end notebooks for: ◆Data analysis ◆Data visualization ◆Data cleaning ◆Classical ML ◆Computer vision ◆Natural3.4×02.2k6231.2k
52Nov 10, '22Advanced NLP - Carnegie Mellon 2022 Advanced NLP is one of the best NLP courses on the web. While most courses cover ancient stuff, this course covers current state-of-the-art tech3.4×01.9k4321.5k
53Feb 13, '23Algebra, Topology, Differential Calculus, and Optimization Theory For Computer Science and Machine Learning - Jean Gallier, UPenn A comprehensive book that covers math theories rel3.4×63k859199389
54Aug 19, '22First Principles of Computer Vision, Columbia University Really nice lectures on the physical and mathematical foundations of computer vision. 140 videos that you can watch at your3.3×02k3581.5k
55Jun 19, '25Stanford CS336 - Language Modeling from Scratch Excellent new lectures on "language modelling from scratch" class from Stanford just dropped. Covers a whole LLM stack from data col3.2×60k8201381.2k
56Apr 20, '23Transformer Math 101 An excellent blog post about basic math related to computation and memory usage for transformers. Nicely explained!!3.2×59k706196375
57Mar 11, '23MIT Introduction to Deep Learning - 2023 Edition is Live! MIT Intro to DL is one of the most concise AI courses on the web that cover basic deep learning techniques, architectures,3.0×57k776212324
58Aug 6, '22DeepMind & UCL Deep Learning Lecture Series 12 lectures on different deep learning algorithms and techniques in natural language processing, vision, generative modeling, etc...3.0×01.9k3811.3k
59Mar 15, '23Multimodal Machine Learning - Carnegie Mellon, 2022 A great series of lectures on multimodal machine learning(MML). The course covers fundamental concepts related to MML and recent2.9×53k689229345
60Oct 7, '22Awesome Diffusion Models A fantastic and well-organized collection of learning resources on diffusion models such as introductory papers, survey papers, intro videos, long lectures2.8×01.7k3801.2k
61Sep 13, '22Machine Learning for Intelligent Systems - Cornell CS4780 ~37 great lectures covering a wide range of algorithms and techniques in classical machine learning & deep learning. L2.7×01.5k3731.2k
62Oct 28, '25Reinforcement Learning of Large Language Models, Spring 2025(UCLA) Great set of new lectures on reinforcement learning of LLMs. Covers a wide range of topics related to RLxLLMs suc2.3×43k820114962
63Oct 5, '22Deep Learning Systems 2022 - Carnegie Mellon CMU is offering a DL systems course for free online. The course is about understanding the internals of deep learning frameworks and bu2.1×01.2k298901
64Oct 29, '22Deep Learning Course, University of Geneva A great deep learning intro course that covers various neural network architectures(ConvNets, MLPs, RNNs, attention, generative models) &2.1×01.2k281921
65Nov 26, '22Deep Learning for Computer Vision - Justin Johnson at Michigan THIS is inarguably one of the best(if not the best) deep learning & computer vision courses. The course covers es2.1×01.1k249961
66Feb 26, '22A free online book that covers all basic data science and machine learning tools: - NumPy - Seaborn - Matplotlib - Pandas - Scikit-Learn Python Data Science Handbook:2.0×01.6k401566
67May 13, '22Announcement 🚀🚀 ----------------- Complete Machine Learning Package is now live on the web. You can now browse all materials seamlessly and view all 35 notebooks without any prob2.0×01.3k348688
68Oct 8, '21The machine learning research community is very and very vibrant. Here is what I mean...🧵🧵2.0×01.3k358623
69Jul 5, '22First Principles of Computer Vision, Columbia University Really nice lectures on the physical and mathematical foundations of computer vision. 140 videos that you can watch at your1.8×01.2k276619
70Nov 1, '22Deep Learning - UCB Berkeley 2021 A great series of deep learning lectures that cover ML basics, error analysis, neural networks training mechanics, and architectures(in vision, NL1.7×0996261755
71Oct 25, '22First Principles of Computer Vision, Columbia University Really nice lectures on the physical and mathematical foundations of computer vision. 140 videos that you can watch at your1.7×0954206799
72Jul 19, '21PCA is an unsupervised learning algorithm that is used to reduce the dimension of large datasets. For such reason, it's commonly known as a dimensional reduction algorithm. PCA is 1.6×01.4k206397
73May 25, '22MLOps or Machine Leaning Operations is one of the most important things to be studying these days. Building models is one thing. Making models useful is another thing. The reason w1.6×01k202642
74Nov 14, '22Computational Linear Algebra for Coders - FAST DOT AI A great maths course taught with "top-down approach", much like Practical DL for Coders. Taught in Python, uses basic librarie1.5×0830209677
75Sep 24, '21Updates on what's coming up this weekend 🚀🚀 A MACHINE LEARNING COMPLETE PACKAGE containing 27+ end-to-end notebooks for: ◆Data analysis and cleaning ◆Data visualization ◆Classica1.5×01.1k207496
76Nov 24, '22DeepMind & UCL Deep Learning Lecture Series 12 lectures on various deep learning algorithms and techniques in natural language processing, vision, generative models, etc. All l1.4×0797207630
77Oct 3, '22How diffusion models work: the math from scratch | AI Summer A great article on diffusion models by AI summer(@theaisummer). Diffusion models have been the primary building block o1.4×0890171605
78Oct 18, '21Kaggle's 2021 State of Data Science and Machine Learning survey was released a few days ago. If you didn't see it, here are some important takeaways 🧵1.3×0934254405
79Oct 8, '22Deep Unsupervised Learning - UC Berkeley Most ML tasks require labeled data, but the vast amount of data in the world are not labeled. This course covers modern unsupervised techni1.3×0788179535
80Aug 1, '22UC Berkely Deep Unsupervised Learning Most ML tasks are supervised(require labeled data), but with the massive amount of unlabeled data freely available today, unsupervised methods1.3×0845189501
81Jun 5, '22A single lecture from Stanford CS230 that will teach you how to: - Read research papers effectively - What to do after you have got DL foundations - Build interesting projects - St1.2×0807180495
82Mar 3, '22Introduction to Computer Science and Programming in Python - MIT 6.0001 An applied & beginner-friendly introduction to common computer science concepts & techniques in Pyth1.2×0874237388
83Oct 4, '22Stanford CS 330: Deep Multi-Task and Meta Learning A great course for people interested in multi-task learning, meta learning, reinforcement learning, lifelong learning, etc... All1.2×0812159498
84Aug 25🧵New Paper: Reasoning models now think out loud for thousands of tokens, often correcting themselves, testing hypotheses, and hedging. But are these behaviors actually associated 1.2×23k962173
85Apr 15, '22The all-time 4 papers that revolutionalized deep learning, computer vision, and NLP in the last decade 🧵🧵1.2×0849161463
86Aug 6, '21Machine learning complete toolset: ◆NumPy ➙ Numeric computations ◆Pandas ➙Data analysis & manipulation ◆Matplotlib/Seaborn ➙data viz ◆Scikit-Learn ➙Classical ML algorithms ◆Ten1.2×01k222302
87Jun 12, '22DeepMind & UCL Deep Learning Lecture Series 12 lectures on different deep learning algorithms and techniques in natural language processing, vision, generative models, etc... A1.2×0837208406
88Aug 11, '22MIT Deep Learning for Art, Aesthetics, and Creativity Generating photorealistic images and arts has been the highlight of AI in 2022. This is a great course for people interested i1.2×0820166437
89Aug 1, '21Python in one pic Credits: Uknown1.2×01k184293
90Mar 10, '22MIT 6.S191 Introduction to Deep Learning is one of the concise deep learning courses that are available on the web! 10 lectures, each an hour or less but still convey all things yo1.2×0868219345
91Jun 11, '22LSTM is dead. Long Live Transformers This is one of the best talks that explain well the downsides of Recurrent Networks and dive deep into Transformer architecture.1.1×0779151444
92Nov 9, '22MIT - Computational Systems Biology: Deep Learning in the Life Sciences A great course that covers foundations and state-of-the-art machine learning techniques & algorithms in 1.1×0689153470
93Oct 22, '22Stanford CS330: Deep Multi-Task & Meta Learning 2021 - New Lectures 🥳 CS330 is a freely available course that covers a number of topics related to multi-task & meta-learni1.1×0704150467
94Jan 4, '22Today, you can get started with data science with Python Data Science Handbook. It is beginner-friendly and an intensive book that covers the fundamentals of data science and tools1.1×0746229345
95May 7, '22I am currently putting all materials of the Complete ML Package into a site that can be easily navigable. Stay tuned! I will probably get this done in a few days.1.1×0991170285
96Aug 20, '21Python Data Science Handbook is a fantastic and in-depth data science book that is entirely available online. For free! It covers NumPy, Pandas, Matplotlib, and Scikit-Learn. Thank1.1×0872209294
97Jul 15, '21Here is a Machine Learning complete toolset: ◆NumPy ➙Computation ◆Pandas ➙Data analysis & manipulation ◆Matplotlib/Seaborn ➙data viz ◆Scikit-Learn ➙Classical ML & data prep1.0×0892190249
98Jun 27, '22Deep Learning Course, University of Geneva I lately came across this course and glanced through the materials and was stunned by the course notes and presentations. Really nice dee1.0×0696184335
99Jan 15, '22"We need to shift our mindset from big data to good data." - Andrew Ng0.9×01.1k16524
100Apr 28, '22A brief history of deep learning0.8×0695165199
101Oct 28, '21The difference between academia and industry0.6×06909436

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