Jean de Nyandwi @Jeande_d Twitter profile

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Jean de Nyandwi

11 months

A NEW ARTICLE 🔥🔥 The first article of Deep Learning Revision Research Blog(introduced recently) is out: "The Transformer Blueprint: A Holistic Guide to the Transformer Neural Network Architecture". In the article, we discuss the core mechanics of transformer neural…

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Jean de Nyandwi

@Jeande_d

1 year

Statistics 110: Probability - Harvard Inarguably, one of the classic/world's best probability courses on the web!!

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Jean de Nyandwi

@Jeande_d

2 years

You 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 Handbook - Probabilistic Machine Learning - Machine Learning Yearning Here are their links 🧵

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Jean de Nyandwi

@Jeande_d

1 year

Applied 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 notebooks (and as slides)". 80 videos. Videos: Code:

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Jean de Nyandwi

@Jeande_d

2 years

Applied 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 notebooks (and as slides)" Lectures: Notebooks:

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Jean de Nyandwi

@Jeande_d

2 years

Statistics 110: Probability - Harvard Inarguably, one of the classic probability courses on the web!!

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Jean de Nyandwi

@Jeande_d

1 year

MIT 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, and applications. 2023 lectures are starting in just one day, Jan 9th!

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Jean de Nyandwi

@Jeande_d

3 years

Releasing a complete machine learning package containing over 30 end to end notebooks for: ◆Data analysis ◆Data visualization ◆Data cleaning ◆Classical ML ◆Computer vision ◆Natural language processing Everything is now accessible here:

GitHub - Nyandwi/machine_learning_complete: A comprehensive machine learning repository containing...

A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques. - Nyandwi/machine_learning_complete

github.com

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Jean de Nyandwi

@Jeande_d

1 year

Machine Learning Engineering for Production (MLOps) - DeepLearningAI Building models is one thing. Making them useful is another thing. The first course of the MLOps specialization teaches the ML lifecycle & deploying models. Course 1 is free on Youtube:

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Jean de Nyandwi

@Jeande_d

1 year

The 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 architectures, training models, synthesis(generative AI), etc... And it's free:

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Jean de Nyandwi

@Jeande_d

1 year

Deep 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(CNNs, transformers, GNNs), generative networks, and contrastive learning.

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Jean de Nyandwi

@Jeande_d

2 years

First 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 your pace. Slides are also provided to follow along.

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Jean de Nyandwi

@Jeande_d

2 years

Advanced 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 techniques & algorithms in modern NLP. Good course materials as well! Videos:

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Jean de Nyandwi

@Jeande_d

2 years

DeepMind & UCL Deep Learning Lecture Series 12 lectures on different deep learning algorithms and techniques in natural language processing, vision, generative modeling, etc... All lectures and presentations are free and you can take them at your pace.

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Jean de Nyandwi

@Jeande_d

1 year

Stanford 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 there are pointers for recent/landmark papers in LLMs.

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Jean de Nyandwi

@Jeande_d

1 year

Stanford 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, life-long learning, unsupervised pretraining, etc... Lecture videos:

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Jean de Nyandwi

@Jeande_d

2 years

Awesome Diffusion Models A fantastic and well-organized collection of learning resources on diffusion models such as introductory papers, survey papers, intro videos, long lectures, and blog posts. Papers in vision, natural language, tabular, graph, etc.

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Jean de Nyandwi

@Jeande_d

1 year

Applied 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 notebooks (and as slides)". Lectures: Notebooks:

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Jean de Nyandwi

@Jeande_d

1 year

[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. Materials for the new course are now freely available. No Matlab, just Python!

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Jean de Nyandwi

@Jeande_d

1 year

Understanding 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 really nice. Get the book draft: Book website:

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Jean de Nyandwi

@Jeande_d

2 years

A free online book that covers all basic data science and machine learning tools: - NumPy - Seaborn - Matplotlib - Pandas - Scikit-Learn Python Data Science Handbook:

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Jean de Nyandwi

@Jeande_d

1 year

Deep Learning and Computational Physics - Lecture Notes, University of South California Great & concise notes on various fundamental topics in deep learning. The notes got a nice structure. Starts from the very basics, gradually to some DL architectures.

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Jean de Nyandwi

@Jeande_d

2 years

Machine Learning for Intelligent Systems - Cornell CS4780 ~37 great lectures covering a wide range of algorithms and techniques in classical machine learning & deep learning. Lectures: Notes:

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Jean de Nyandwi

@Jeande_d

3 years

PCA 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 one of these useful things that is not talked about. But there is a reason 👇

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Jean de Nyandwi

@Jeande_d

1 year

Introduction 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 theories, techniques & algorithms that are used in present times. Lectures:

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Jean de Nyandwi

@Jeande_d

8 months

The 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 fundamentals, efficient computation, training deep models, architectures, applications, and generative tasks.…

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Jean de Nyandwi

@Jeande_d

2 years

Announcement 🚀🚀 ----------------- Complete Machine Learning Package is now live on the web. You can now browse all materials seamlessly and view all 35 notebooks without any problem, whether on desktop or mobile. It's here:

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Jean de Nyandwi

@Jeande_d

3 years

The machine learning research community is very and very vibrant. Here is what I mean...🧵🧵

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Jean de Nyandwi

@Jeande_d

1 year

AI 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(like PyTorch, Lightning, Hugging Face, and more). Course book:

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Jean de Nyandwi

@Jeande_d

1 year

Intro 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 learning algorithms. A good start to 2023 for people looking for something new!

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Jean de Nyandwi

@Jeande_d

1 year

Everything 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:

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Jean de Nyandwi

@Jeande_d

2 years

First 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 your pace. Slides are also provided to follow along.

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Jean de Nyandwi

@Jeande_d

2 years

Deep 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 building them from scratch. Website: Past lectures:

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Jean de Nyandwi

@Jeande_d

2 years

Deep Learning Course, University of Geneva A great deep learning intro course that covers various neural network architectures(ConvNets, MLPs, RNNs, attention, generative models) & techniques for training them. Really good notes & slides! DL course:

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Jean de Nyandwi

@Jeande_d

1 year

Introduction 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, neural networks techniques & algorithms, and latest advances in the field.

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Jean de Nyandwi

@Jeande_d

2 years

"We need to shift our mindset from big data to good data." - Andrew Ng

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Jean de Nyandwi

@Jeande_d

2 years

Deep 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 essential deep learning techniques and modern visual recognition architectures.

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Jean de Nyandwi

@Jeande_d

1 year

Advanced 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 materials were just uploaded recently!! Lectures: Website:

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Jean de Nyandwi

@Jeande_d

3 years

Updates 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 ◆Classical ML ◆Computer vision ◆NLP LAUNCH DATE: Sunday, 26th, 2021 Cost: Free via Github

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Jean de Nyandwi

@Jeande_d

3 years

Machine learning complete toolset: ◆NumPy ➙ Numeric computations ◆Pandas ➙Data analysis & manipulation ◆Matplotlib/Seaborn ➙data viz ◆Scikit-Learn ➙Classical ML algorithms ◆TensorFlow/PyTorch ➙Neural nets ◆TensorBoard ➙Debugging ◆TensorFlow Extended ➙Deployment

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Jean de Nyandwi

@Jeande_d

3 years

Python in one pic Credits: Uknown

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Jean de Nyandwi

@Jeande_d

1 year

Reproducible 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 & Git & Github, testing, debugging, finding & fixing tools bugs, etc. Playlist:

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Jean de Nyandwi

@Jeande_d

1 year

The 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:

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Jean de Nyandwi

@Jeande_d

2 years

Deep 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, NLP, generative, RL). 66 videos. Available freely. Self-paced

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Jean de Nyandwi

@Jeande_d

2 years

MLOps 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 why you need to study MLOps and the 4 learning resources that you will ever need 🧵🧵

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Jean de Nyandwi

@Jeande_d

2 years

I 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.

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Jean de Nyandwi

@Jeande_d

1 year

Advanced Natural Language Processing - Class Notes, University of Southern California Great and concise notes on various techniques and algorithms in natural language processing. Notes: Course webpage:

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Jean de Nyandwi

@Jeande_d

9 months

TinyML 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 topics covered include model compression, pruning, quantization, neural architecture search,…

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Jean de Nyandwi

@Jeande_d

1 year

Deep Learning , University of Liège A nice collection of lectures on various deep learning topics such as deep learning foundations, training neural networks, architectures, etc... Lectures: GitHub:

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Jean de Nyandwi

@Jeande_d

3 years

Kaggle'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 🧵

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Jean de Nyandwi

@Jeande_d

9 months

Vision 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 transformation is truly a "masterly at play".

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Jean de Nyandwi

@Jeande_d

10 months

Natural 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, BART, T5, GPT-3...), and hot topics/trends in LLMs including instruction tuning, chain-of-thoughts,…

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Jean de Nyandwi

@Jeande_d

10 months

[Lecture notes] Stanford CS324 - Large Language Models Excellent notes on various topics related to large language models: fundamentals of language models, capabilities of LLMs, data behind LLMs, modeling, training, scaling laws, selective architectures, task adaptation, and…

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Jean de Nyandwi

@Jeande_d

1 year

Advanced 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 is one of the most valuable applications of machine learning. Lectures:

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Jean de Nyandwi

@Jeande_d

1 year

Multimodal 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 generate images from texts, robotic actions from language & images, etc.

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Jean de Nyandwi

@Jeande_d

3 years

Python 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. Thanks to @jakevdp for making this great book free.

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Jean de Nyandwi

@Jeande_d

2 years

First 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 your pace. Slides are also provided to follow along ⬇️⬇️

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Jean de Nyandwi

@Jeande_d

3 years

Here is a Machine Learning complete toolset: ◆NumPy ➙Computation ◆Pandas ➙Data analysis & manipulation ◆Matplotlib/Seaborn ➙data viz ◆Scikit-Learn ➙Classical ML & data preps ◆TensorFlow/PyTorch ➙Neural nets ◆TensorBoard ➙Debugging ◆TensorFlow Extended ➙Deployment

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Jean de Nyandwi

@Jeande_d

2 years

Introduction to Computer Science and Programming in Python - MIT 6.0001 An applied & beginner-friendly introduction to common computer science concepts & techniques in Python YT playlist: Syllabus, slides, codes:

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Jean de Nyandwi

@Jeande_d

10 months

Stanford 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 available to the public recently. The course covers a wide range of topics from supervised learning,…

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Jean de Nyandwi

@Jeande_d

1 year

Understanding Deep Learning A great textbook that covers foundations of deep learning, techniques for training neural networks, and modern neural network architectures(CNNs, Transformers, GNNs, GANs, diffusion models, deep RL, etc). Get your copy(WIP):

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Jean de Nyandwi

@Jeande_d

2 years

How 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 of first-class works in image generation and beyond. Worth reading about!!

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Jean de Nyandwi

@Jeande_d

2 years

MIT 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 you need to know! 2022 course is starting this Friday. Learn more:

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Jean de Nyandwi

@Jeande_d

1 year

Neural Networks: Zero to Hero - Andrej Karpathy A growing series of lectures on various fundamental neural network techniques and architectures. From backward prop, MLPs, language modeling, and more to come. Lecture videos: Code:

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Jean de Nyandwi

@Jeande_d

1 year

Algebra, Topology, Differential Calculus, and Optimization Theory For Computer Science and Machine Learning - Jean Gallier, UPenn A comprehensive book that covers math theories related to CS and machine learning. Very intense, 2163 pages!!! Get a copy:

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Jean de Nyandwi

@Jeande_d

2 years

UC Berkely Deep Unsupervised Learning Most ML tasks are supervised(require labeled data), but with the massive amount of unlabeled data freely available today, unsupervised methods such as self-supervised learning(SSL) are hot topics these days.

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Jean de Nyandwi

@Jeande_d

2 years

The all-time 4 papers that revolutionalized deep learning, computer vision, and NLP in the last decade 🧵🧵

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Jean de Nyandwi

@Jeande_d

2 years

Computational 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 libraries(NumPy, Scikit-Learn) & PyTorch. Videos: Code:

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Jean de Nyandwi

@Jeande_d

2 years

DeepMind & UCL Deep Learning Lecture Series 12 lectures on different deep learning algorithms and techniques in natural language processing, vision, generative models, etc... All lectures and presentations are free and you can take them at your pace.

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Jean de Nyandwi

@Jeande_d

2 years

MIT 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 in using deep learning for creativity. Covering AI + creativity, GANs, diffusion models, etc.

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Jean de Nyandwi

@Jeande_d

1 year

MIT 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 foundations of deep learning, neural net architectures, and applications of DL.

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Jean de Nyandwi

@Jeande_d

2 years

A 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 - Structure your ML career - Do meaningful work

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career...

Andrew Ng, Adjunct Professor & Kian Katanforoosh, Lecturer - Stanford Universityhttp://onlinehub.stanford.edu/Andrew NgAdjunct Professor, Computer ScienceKia...

www.youtube.com

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Jean de Nyandwi

@Jeande_d

2 years

Stanford 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... All course lectures & guest lectures are available publicly:

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Jean de Nyandwi

@Jeande_d

11 months

This 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 guides from the Cookbook: - How to count tokens with tiktoken: - How to…

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Jean de Nyandwi

@Jeande_d

2 years

Deep 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 techniques that are used for learning from unlabelled datasets!

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Jean de Nyandwi

@Jeande_d

2 years

DeepMind & UCL Deep Learning Lecture Series 12 lectures on various deep learning algorithms and techniques in natural language processing, vision, generative models, etc. All lectures & presentations are amazing, free and you can take them at your pace.

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Jean de Nyandwi

@Jeande_d

1 year

MIT 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, and applications. 2023 edition just started!! Lecture 1(Intro to DL):

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Jean de Nyandwi

@Jeande_d

2 years

LSTM 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.

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Jean de Nyandwi

@Jeande_d

1 year

A 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 techniques/concepts of the RL field.

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Jean de Nyandwi

@Jeande_d

2 years

Today, 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 tools such as NumPy, Matplotlib, Seaborn, and Scikit-Learn. Free on the web.

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Jean de Nyandwi

@Jeande_d

11 months

Code 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, etc...), who can answer your questions with beautiful visualizations, who can code, etc... Like many…

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Jean de Nyandwi

@Jeande_d

9 months

[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 2023 iteration are public now. The course covers fundamental techniques and topics related to deep…

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Jean de Nyandwi

@Jeande_d

11 months

Long-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 with commonly used programming language in data world. Get your (free) copy here:…

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Jean de Nyandwi

@Jeande_d

1 year

Pen 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 linear algebra, optimization, graphical models and etc... This is a relevant resource for anyone who…

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Jean de Nyandwi

@Jeande_d

3 years

The difference between academia and industry

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Jean de Nyandwi

@Jeande_d

1 year

Everything is Connected: Graph Neural Networks Graphs Neural Networks(GNNs) are increasingly showing potential in modeling graphs datasets. @PetarV_93 just published a survey paper on key concepts in GNNs. This is an excellent resource for learning GNNs.

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Jean de Nyandwi

@Jeande_d

1 year

Transformer Math 101 An excellent blog post about basic math related to computation and memory usage for transformers. Nicely explained!!

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Jean de Nyandwi

@Jeande_d

2 years

Stanford 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-learning such as transfer learning, life-long learning, unsupervised pretraining, etc...

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Jean de Nyandwi

@Jeande_d

2 years

A brief history of deep learning

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Jean de Nyandwi

@Jeande_d

2 years

Deep 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 deep learning introductory course covering various techniques and algorithms

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Jean de Nyandwi

@Jeande_d

2 years

Early last year, I wanted to learn about Machine Learning Operations(MLOps). MLOps refers to the whole processes involved in building and deploying machine learning models reliably. A thread on the importance of MLOps and resources that I used 🧵

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Jean de Nyandwi

@Jeande_d

2 years

Stanford CS25 - Transformers United A new class of Transformers and their applications in NLP, vision, RL, Biology, audio & speech. 9 lecture videos are available already!! Youtube: Website:

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Jean de Nyandwi

@Jeande_d

2 years

MIT - 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 genomics & life sciences. Covers deep learning & classical ML approaches, etc.

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Jean de Nyandwi

@Jeande_d

1 year

Multimodal Machine Learning - Carnegie Mellon, 2022 A great series of lectures on multimodal machine learning(MML). The course covers fundamental concepts related to MML and recent state-of-the-art MML systems. Lectures: Webpage:

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Jean de Nyandwi

@Jeande_d

3 years

The most useful courses are free. They are only challenging and hard to complete, which is why they are useful. Here are 4 examples of the free machine learning courses that with enough dedication can help you get useful skills. 🧵

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Jean de Nyandwi

@Jeande_d

10 months

LLaMA2 came with this well-curated guide that includes best practices and resources for working with large language models, LLaMA in particular. This guide is a relevant resource for practitioners and developers(or basically anyone building with LLMs) as it covers important…

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Jean de Nyandwi

@Jeande_d

1 year

PyTorch Tools, best practices & Styleguide A nice repository that provides best practices and tips in Python and PyTorch. From code editors, scripts vs notebooks, libraries, organization of project files, sample neural networks, do's & don't's, FAQs, etc

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Jean de Nyandwi

@Jeande_d

3 years

Machine Learning has transformed many industries, from banking, healthcare, production, streaming, to autonomous vehicles. Here are examples of how that is happening👇

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Jean de Nyandwi

@Jeande_d

2 years

Advanced Robotics - UC Berkeley Friends in robotics, here is a great course that covers advanced topics & concepts in robotics: maths, algorithms, state-of-the-art robotic systems, etc... Lectures: Website:

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Jean de Nyandwi

@Jeande_d

1 year

How to avoid machine learning pitfalls: a guide for academic researchers A really nice guide on doing machine learning the right way. Covers nearly all machine learning stages(before/after modeling, evaluation,...) and do's & don'ts in each stage.

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Jean de Nyandwi

@Jeande_d

2 years

If I was starting my machine learning journey, I would early on - Learn Python well - Learn ML fundamentals, algorithms & essential tools(NumPy, Pandas, Scikit-Learn) well - Practice on Kaggle - Learn Git - Contribute to open-source tools - Make peace with not knowing everything

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