ML: Machine Learning,
DL: Deep Learning,
NLP: Natural Language Processing,
RL: Reinforcement Learning,
CV: Computer Vision,
NN: Neural Networks.
DS: Data Science
SDC: Self-Driving Car
| Topic | Institute | Name | Year(s) | Youtube Link | Course Website | OK |
|---|---|---|---|---|---|---|
| AI | UC Berkeley | CS188 Intro to AI | 2018-2023 | 2018 and 2023 | HomePage and 2018 and 2023 | 76% |
| AI | Stanford | CS221 AI: Principles and Techniques | 2019-2022 | 2019 and 2021 | 2019 and 2021 | |
| ML | Stanford | CS229: ML | 2018-2022 | 2018 taught by Andrew NG, and 2022 | ~ | |
| ML | DeepLearning.Ai | ML Specialization | ~ | link | ~ | |
| ML | DeepLearning.Ai | ML Ops | ~ | link | ~ | |
| ML | Stanford | CS224W: Machine Learning with Graphs | ~ | link | ~ | |
| ML | Caltech | Learning From Data | 2012 | link | link | |
| ML | Cornell | Applied ML | 2020 | link | link | |
| ML | UC Berkeley | CS294: Deep Unsupervised Learning | 2020 | link | link | |
| DL | Stanford | CS230: DL | 2018 | link | ~ | |
| DL | New York University | DL | 2020-2021 | with Yann LeCun: 2020, and 2021 | ~ | |
| DL | Fast.AI | Practical DL for coders | ~ | part 1: DL, and part 2: Stable Diffusion and DL | link | |
| DL | DeepLearning.Ai | DL Specialization | ~ | 1: NN & DL, 2: Improving Deep NN, 3: Structuring ML Projects, 4: Convolutional NN, and 5: Sequence Models | ~ | |
| DL | Google DeepMind x University College London | DL | 2018-2020 | 2018, and 2020 | ~ | |
| DL | Stanford | CS330: Deep Multi-Task and Meta Learning | 2019-2023 | 2019 and 2023 | link | |
| DL | MIT | 6.S191 Intro to DL | ~ | link | ~ | |
| DL | MIT | 6.5940 TinyML and Efficient Deep Learning Computing | 2023 | link | ~ | |
| DL | MIT | Deep Learning in Life Sciences 6.874 | 2020 | link | link | |
| DL | UC Berkeley | CS 182: Deep Learning | 2021 | link | link | |
| NLP | Stanford | CS224N: NLP with DL | 2021-2023 | 2021, and 2023 | ~ | |
| NLP | Stanford | XC224U: NLP Understanding | 2021-2023 | 2021, and 2023 | ~ | |
| NLP | Fast.ai | A Code-First Introduction to NLP | 2019 | link | link | |
| NLP | UMass | CS685: Advanced NLP | 2023 | link | ~ | |
| NLP | University of Texas at Austin | NLP | 2023 | link | ~ | |
| NLP | CMU | Advanced NLP | 2021-2024 | 2021, 2022, and 2024 | 2024 | |
| RL | Stanford | CS234: RL | 2019 | link | ~ | |
| RL | DeepMind x UCL | RL | 2015-2021 | 2015, 2018, and 2021 (youtube playlist name is wrong) | ~ | |
| RL | UC Berkeley | CS 285: Deep Reinforcement Learning | 2020-2023 | 2020 and 2023 | link | |
| CV | UC Berkeley | CS 198-126: Deep Learning for Visual Data | 2022-2024 | 2022, 2023, 2024 | web | |
| CV | Stanford | CS231N: DL for CV | 2016-2017 | 2016, 2017 | 2017, 2024 | |
| CV | Michigan Online | DL for CV | ~ | link | link | |
| CV | University of Central Florida | CV | 2014 | link | ~ | |
| CV | University of Tübingen | CV | 2023 | link | link | |
| CV | Weizmann Institute of Science | DL for CV: Fundamentals and Applications | 2021 | 2021 and 2023 | link | |
| CV | University of Washington | The Ancient Secrets of Computer Vision | 2018 | youtube | link | |
| Robotics | UC Berkeley | CS287 Advanced Robotics | 2019 | link | scroll down after opening this link | |
| SDC | University of Tübingen | Self-Driving Cars | 2023 | link | link | |
| Math | Stanford | CS109 Introduction to Probability for Computer Scientists | 2023 | link | link | |
| Math | Stanford | EE364A Convex Optimization | 2021-2024 | 2021 covid ,2024 | link | |
| Math | University of Tübingen | Math for Deep Learning | 2022 | link | link | |
| Big Data | Stanford | CS246 Mining Massive Data Sets | 2016-2020 | yt-2016, yt-2020 | mmds, stanford web | ~ |
| Other | Stanford | CS25 Transformers United | ~ | link | ~ | |
| Other | Stanford | CS236: Deep Generative Models | 2023 | youtu | web lin |
| Topic | Playlist Name | Channel Name | Year | Youtube Link | OK |
|---|---|---|---|---|---|
| ML | ML | StatQuest with Josh Starmer | 2018 | link | |
| ML | Linear Regression and Linear Models | StatQuest with Josh Starmer | 2017 | link | |
| ML | Machine Learning with Python | Sentdex | 2016 | link | |
| ML | Scikit-learn Machine Learning with Python and SKlearn | Sentdex | 2015 | link | |
| ML | ML in Python with scikit-learn | Data School | 2015 | link | |
| ML | Intro to Machine Learning and Statistical Pattern Classification Course | Sebastian Raschka | 2021 | link | 3/95 |
| ML | Intelligence and Learning | The Coding Train | 2018 | link | |
| ML | ML For Beginners | codebasics | 2018 | link | |
| DL | Neural networks | 3Blue1Brown | 2018 | link | |
| DL | Neural Networks: Zero to Hero | Andrej Karpathy | 2022 | link | |
| DL | Intro to Deep Learning and Generative Models Course | Sebastian Raschka | 2021 | link | |
| DL | Neural Networks/ Deep Learning | StatQuest with Josh Starmer | 2022 | link | |
| DL | Foundations of Deep RL | Pieter Abbeel | 2021 | link | |
| DL | Deep Learning Fundamentals - Intro to Neural Networks | deeplizard | 2017 | link | |
| DL | Deep Learning With Tensorflow 2.0, Keras and Python | codebasics | 2020 | link | |
| RL | Reinforcement Learning - Developing Intelligent Agents | deeplizard | 2018 | link | |
| CV | OpenCV with Python for Image and Video Analysis | Sentdex | 2016 | link | |
| CV | OpenCV Course - Full Tutorial with Python | freeCodeCamp.org | 2020 | link | |
| CV | Computer Vision in Practice | Roboflow | 2023 | link | |
| CV | DL for CV (neuralearn.ai) | freeCodeCamp.org | 2023 | link | |
| CV | OpenCV Python Tutorials | Tech With Tim | 2021 | link | |
| NLP | NLTK with Python 3 for Natural Language Processing | Sentdex | 2016 | link | |
| NLP | NLP Transformers Attention | ~ | ~ | link | |
| NLP | NLP Tutorial Python | codebasics | 2023 | link | |
| GAN | Generative Adversarial Networks (GANs) | Ahlad Kumar | 2019 | link | |
| Python | Python for Beginners | freeCodeCamp.org | 2022 | link | |
| Python | Python Tutorials | Corey Schafer | 2016-2021 | link | |
| Python | Intermediate Python Tutorials | Tech With Tim | 2018 | link | |
| Python | Expert Python Tutorials | Tech With Tim | 2020 | link | |
| Python | Python Intermediate Tutorial | NeuralNine | 2019 | link | |
| Python | Python Advanced Tutorials | NeuralNine | 2021 | link | |
| PyTorch | PyTorch Tutorials | Aladdin Persson | 2021 | link | |
| PyTorch | PyTorch for Deep Learning & Machine Learning | freeCodeCamp.org | 2022 | Youtube, Course Materials | |
| PyTorch | PyTorchZeroToAll (in English) | Sung Kim | 2017 | link | |
| PyTorch | PyTorch - Python Deep Learning Neural Network API | deeplizard | 2018 | link | |
| TensorFlow | TensorFlow 2.0 Beginner Tutorials | Aladdin Persson | 2021 | link | |
| TensorFlow | TensorFlow 2.0 Complete Course | freeCodeCamp.org | 2020 | link | |
| TensorFlow | Building recommendation systems with TensorFlow | TensorFlow | 2021 | link | |
| TensorFlow | TensorFlow - Python Deep Learning Neural Network API | deeplizard | 2020 | link | |
| Keras | Keras Python Deep Learning Neural Network API | deeplizard | 2017 | link | |
| Keras & TensorFlow | Deep Learning Deployment Basics - Neural Network Web Apps | deeplizard | 2022 | link | |
| Sikit-Learn | scikit-learn tips | Data School | 2020 | link | |
| Matplotlib | Matplotlib Tutorials | Corey Schafer | 2019 | link | |
| Matplotlib | Matplotlib Tutorial Series - Graphing in Python | Sentdex | 2016 | link | |
| Flask | Practical Flask Web Development Tutorials | Sentdex | 2016 | link | |
| Flask | Flask Tutorials | Corey Schafer | 2018 | link | |
| Flask | Flask | Krish Naik | 2021 | link | |
| Flask | Flask Blog Tutorial | Tech With Tim | 2021 | link | |
| Flask | Flask Tutorials | Tech With Tim | 2021 | link | |
| Flask | CS50x 2024 - Lecture 9 - Flask | CS50 | 2024 | link | |
| Backend | Learn Python Backend Development by Building 3 Projects | freeCodeCamp.org | 2024 | link | |
| Pandas | Data analysis in Python with pandas | Data School | 2016 | link | |
| Pandas | Pandas Tutorials | Corey Schafer | 2020 | link | |
| Pandas | Pandas Tutorial (Data Analysis In Python) | codebasics | 2017 | link | |
| NumPy | Deep Learning Prerequisites: The Numpy Stack in Python | Lazy Programmer | 2020 | link | |
| NumPy | Python NumPy Tutorial for Beginners | freeCodeCamp.org | 2019 | link | |
| Django | Django Tutorials | Corey Schafer | 2019 | link | |
| Django | Django Web Development with Python | Sentdex | 2019 | link | |
| Django | Python Django Tutorials | Tech With Tim | 2020 | link | |
| Django | Django Tutorial (Create a Blog) | Net Ninja | 2017 | link | |
| [ Django | Django Tutorials for Beginners | thenewboston | 2016 | link | |
| Django | Try Django 3.2 - Python Web Development Tutorial Series | CodingEntrepreneurs | 2021 | link | |
| DB | Complete MongoDB Tutorial | Net Ninja | 2022 | link | |
| Docker | Docker Crash Course Tutorial | Net Ninja | 2022 | link | |
| Docker | Docker Tutorials | thenewboston | 2021 | link | |
| Github | Git & GitHub Tutorial for Beginners | Net Ninja | 2022 | link | |
| Git | Git Tutorials | Corey Schafer | 2016 | link | |
| Web Scraping | Python Selenium Tutorials | Tech With Tim | 2020 | link | |
| Web Scraping | Beautiful Soup 4 Tutorial | Tech With Tim | 2021 | link | |
| Web Scraping | Python Web Crawler Tutorials | thenewboston | 2016 | link | |
| Finance | Python Programming for Finance | Sentdex | 2018 | link | |
| Finance | Python for Finance with Zipline and Quantopian | Sentdex | 2016 | link | |
| Finance | Customizing Matplotlib Graphs and Charts | Sentdex | 2014 | link | |
| Finance | Machine Learning for Forex and Stock analysis and algorithmic trading | Sentdex | 2014 | link | |
| Finance | Python: Mathematics and Stock/Forex/Futures indicators | Sentdex | 2014 | link | |
| Finance | Big Data Analytics & Algorithmic Stock Trading / Backtesting | Sentdex | 2014 | link | |
| Finance | Trading - Advanced Order Types with Coinbase | deeplizard | 2017 | link | |
| Finance | Python For Finance | NeuralNine | 2020 | link | |
| Finance | Python For Finance | Computer Science | 2020-2024 | link | |
| Finance | Building cryptocurrency trading bots | Cryptocurrency Trading | 2017 | link | |
| Finance | Create Binance Bot in Python - Cryptocurrency Trader | Joaquin Roibal | 2018 | link | |
| Finance | CCXT - Advanced Cryptocurrency Trading Bot Development | Joaquin Roibal | 2018 | link | |
| Finance | Triangular Arbitrage Cryptocurrency Coding in Python | Joaquin Roibal | 2018 | link | |
| Finance | Python - Finance - Trading Robot | Sigma Coding | 2020 | link | |
| Finance | Python - Finance - Machine Learning | Sigma Coding | 2019 | link | |
| Finance | Python - Finance - All | Sigma Coding | 2019 | link | |
| Finance | Full Algorithmic Trading Course | TradeOptionsWithMe | 2021 | link | |
| Finance | Algorithmic Trading With Python | CodeTrading | 2021-2024 | link | |
| Crypto | Blockchain For Beginners | Tech With Tim | 2020 | link | |
| Crypto | Ethereum Tutorials | thenewboston | 2022 | link | |
| Robotics | Robotics and the Raspberry Pi | Sentdex | 2015 | link | |
| Math | Statistics Fundamentals | StatQuest with Josh Starmer | 2017 | link | |
| Math | Essence of linear algebra | 3Blue1Brown | 2016 | link | |
| Math | The essence of calculus | 3Blue1Brown | 2017 | link | |
| Math | Differential equations | 3Blue1Brown | 2021 | link | |
| Math | Linear Algebra | Derek Banas | 2020 | link and link2 | |
| Math | Mathematics for ML: Linear Algebra | My CS | 2020 | link | |
| Data Structures | Data Structures Easy to Advanced Course | freeCodeCamp.org | 2019 | link | |
| Data Structures | Redis for Beginners | Net Ninja | 2023 | link | |
| Data Structures | Redis Explained | Redis | 2021 | link | |
| Linux | Linux/Mac Tutorials | Corey Schafer | 2015 | link | |
| Linux | Linux for Programmers | Tech With Tim | 2021 | link | |
| DS | Data Science Full Course For Beginners | codebasics | ~ | link | |
| DS | Machine Learning & Data Science | Derek Banas | 2021 | link | |
| DS | Data Science | Computer Science | 2018-2023 | link | |
| Mobile App | CS50's Mobile App Development with React Native | CS50 | 2018 | link | |
| C++ | C++ | The Cherno | 2017 | link | |
| Game | Game Programming: Season 1 | The Cherno | 2012 | link | |
| React | React tutorial for beginners | Bro Code | 2024 | link | |
| Bio | Biology Lecture Playlist | thenewboston | 2014 | link | |
| CMD | Windows Command Line Tutorials | thenewboston | 2016 | link | |
| Algo | Recursion + Backtracking Course | Kunal Kushwaha | 2021 | link | |
| DevOp | CI/CD Tutorials | TechWorld with Nana | 2021 | link | |
| DevOp | DevOps Concepts explained | TechWorld with Nana | 2022 | link | |
| DevOp | Infrastructure as Code (IaC) Tutorials | TechWorld with Nana | 2021 | link | |
| DevOp | Complete Kubernetes Tutorial for Beginners | TechWorld with Nana | 2020 | link | |
| DevOp | DevOps Tools | TechWorld with Nana | 2021 | link | |
| DevOp | Docker and Kubernetes Tutorial for Beginners | TechWorld with Nana | 2020 | link | |
| DevOp | Docker Tutorial for Beginners | TechWorld with Nana | 2020 | link |
Sentdex website: click here
| Offered by | Course Name(s) | Links | OK |
|---|---|---|---|
| Microsoft | Generative AI for beginners | link, and github repo | |
| Microsoft | ML for beginners | link, and gihub repo | |
| Microsoft | Data Science for beginners | link, and github repo | |
| Microsoft | AI for beginners | link, and github repo | |
| Microsoft | Web Dev for beginners | link, and github repo | |
| Microsoft | IOT for beginners | link, and github repo | |
| Microsoft | Power BI Data Analyst Professional Certificate | coursera | |
| Google Cloud Skills Boost: Machine Learning Engineer Learning Path, Introduction to Generative AI Learning Path, Data Analyst Learning Path, Data Engineer Learning Path, and.. | link | ||
| Launching into Machine Learning | link | ||
| Machine Learning in the Enterprise | link | ||
| TensorFlow on Google Cloud | link | ||
| Feature Engineering | link | ||
| Introduction to AI and Machine Learning on Google Cloud | link | ||
| Production Machine Learning Systems | link | ||
| ML Pipelines on Google Cloud | link | ||
| Machine Learning Operations (MLOps): Getting Started | link | ||
| Computer Vision Fundamentals with Google Cloud | link | ||
| Recommendation Systems on Google Cloud | link | ||
| Introduction to Image Generation | link | ||
| Data Analytics Professional Certificate | coursera | ||
| Kaggle | Intro to Programming, Python, Intro to ML, Pandas, Intermediate ML, Data Visualization, Feature Engineering, Intro to SQL, Advanced SQL, intro to DL, CV, Time Series, Data Cleaning, Intro to AI Ethics, Geospatial Analysis, ML Explainability, and Intro to Game AI and RL | link | |
| Hugging Face | NLP, Deep RL, Audio, Open-Source AI Cookbook, and ML for Games | link | |
| IBM | Data Science Professional Certificate | coursera | |
| IBM | Data Analyst Professional Certificate | coursera | |
| IBM | AI Engineering Professional Certificate: Machine Learning with Python, Introduction to Deep Learning & Neural Networks with Keras, Introduction to Computer Vision and Image Processing, Deep Neural Networks with PyTorch, Building Deep Learning Models with TensorFlow, and AI Capstone Project with Deep Learning | Coursera | |
| IBM | Machine Learning Professional Certificate: Exploratory Data Analysis for Machine Learning, Supervised Machine Learning: Regression and Classification, Unsupervised Machine Learning, Deep Learning and Reinforcement Learning, Machine Learning Capstone | Coursera |
| Bootcamp Name(s) | From | Year(s) | Links | Description |
|---|---|---|---|---|
| ML Zoomcamp | DataTalksClub | 2022 | Github Repo, and Youtube Playlist | ~ |
| Data Engineering Zoomcamp | DataTalksClub | 2022-2023 | Github Repo, and Youtube Playlist | ~ |
| MLOps Zoomcamp | DataTalksClub | 2022-2023 | Github Repo, and Youtube Playlist | ~ |
| Deep Learning Course | Full Stack Deep Learning | 2018-2022 | webPage, and YouTube Playlist: 2021, 2022 | ~ |
| LLM Bootcamp | Full Stack Deep Learning | 2023 | YouTube, and WebPage | ~ |
| Data Analyst Bootcamp | Alex The Analyst | 2020-2024 | Youtube Playlist, and FreeCodeCamp Single Video | Python, Pandas, Tableau, SQL, PowerBI, and Excell |
| Data Analysis with Python | freeCodeCamp.org | 2020 | link | Data Analyst, Jupyter Notebooks, NumPy, Pandas, Data Cleaning, Reading Data, and Python |
| Python for Data Science | freeCodeCamp.org | 2020 | link | Learn Python, Pandas, NumPy, Matplotlib |
| Building LLM-Powered Apps | Weights & Biases | 2023 | link | Learn how to build LLM-powered applications using LLM APIs |
| LangChain & Vector Databases in Production | ActiveLoop | 2023 | link | Learn how to use LangChain and Vector DBs in Production |
| Building Systems with the ChatGPT API | DeepLearning.Ai | 2023 | link | you will learn how to automate complex workflows using chain calls to a large language model |
| Name | Platform | Description | Link |
|---|---|---|---|
| Machine Learning Specialization | Coursera | #BreakIntoAI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng | link |
| Mathematics for Machine Learning and Data Science Specialization | Coursera | Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability | link |
| AI For Everyone | Coursera | AI is not only for engineers. “AI for Everyone”, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today’s AI can – and cannot – do. Finally, you will understand how AI is impacting society and how to navigate through this technological change | link |
| AI for Good Specialization | Coursera | Learn AI's role in addressing complex challenges. Build skills combining human and machine intelligence for positive real-world impact using AI | link |
| Generative AI for Everyone | Coursera | ~ | link |
| Deep Learning Specialization | Coursera | Become a Machine Learning expert. Master the fundamentals of deep learning and break into AI. Recently updated with cutting-edge techniques! | link |
| Natural Language Processing Specialization | Coursera | Break into NLP. Master cutting-edge NLP techniques through four hands-on courses! Updated with the latest techniques in October '21 | link |
| Generative AI with Large Language Models | Coursera | In Generative AI with Large Language Models (LLMs), created in partnership with AWS, you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications | link |
| TensorFlow: Data and Deployment Specialization | Coursera | Browser-based Models with TensorFlow.js, Device-based Models with TensorFlow Lite, Data Pipelines with TensorFlow Data Services, Advanced Deployment Scenarios with TensorFlow | link |
| StanfordOnline: Databases: Relational Databases and SQL | Edx | ~ | link and Youtube Playlist |
| StanfordOnline: Statistical Learning | Edx | Learn some of the main tools used in statistical modeling and data science. We cover both traditional as well as exciting new methods, and how to use them in R and Python. | edx-with-R, edx-with-Python, Youtube-with-R, and Youtube-with-Python |
| Data Visualization with Tableau Specialization | Coursera, UC Davis | Visualize Business Data with Tableau. Create powerful business intelligence reports | link |
| Learn SQL Basics for Data Science Specialization | Coursera, UC David | SQL for Data Science, Data Wrangling, Analysis and AB Testing with SQL, Distributed Computing with Spark SQL, SQL for Data Science Capstone Project | link |
| ICL: Mathematics for Machine Learning Specialization | Coursera, ICL | Mathematics for Machine Learning: Linear Algebra, Multivariate Calculus, and PCA | link |
| Stanford: Introduction to Statistics | Coursera, Stanford | Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning. | link |
| Name | Description | Links |
|---|---|---|
| Hands on train and deploy ML | Predicting crypto price movements is extremely hard. But it is also a great field to show what Machine Learning has to offer. In this tutorial you won't build an ML system that will make you rich. But you will master the MLOps frameworks and tools you need to build ML systems that, together with tons of experimentation, can take you there. With this hands-on tutorial, I want to help you grow as an ML engineer and go beyond notebooks. | Github |
| Data Science & Machine Learning Projects | YouTube Playlist | link |
| 20 Data Science Projects with Source Code for Beginners | Web Page | link |
| Name | Type | Description | Link(s) |
|---|---|---|---|
| Yannic Kilcher | YouTube Playlist | Explaining Research Papers in a short video | Paper Explained, NLP, RL, and DL Architecture |
| diar.ai ML Papers of The Week | GitHub | At DAIR.AI we ❤️ reading ML papers so we've created this repo to highlight the top ML papers of every week. | GitHub Repo and WebPage |
| labml.ai Deep Learning Paper Implementations | Code & Text | This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better. | WebPage and Github Repo |
| Papers With Code | Website | The mission of Papers with Code is to create a free and open resource with Machine Learning papers, code, datasets, methods and evaluation tables. | web and github |
Watching the people learning these same materials with you.
| Topic | Playlist Name | Channel Name | Year | Youtube Link |
|---|---|---|---|---|
| DL | Deep Learning Adventures - Coding in Tensorflow | George Zoto | 2020 | link |
| DL | Deep Learning Adventures - Tensorflow In Practice | George Zoto | 2020 | link |
| DL | Deep Learning Adventures - Kaggle Courses | George Zoto | 2021 | link |
| DL | Deep Learning Adventures - TensorFlow Data and Deployment | George Zoto | 2021 | link |
| Name | Author(s) | Description | Link(s) |
|---|---|---|---|
| ML for Trading - 2nd Edition | Stefen Jansen | This book aims to show how ML can add value to algorithmic trading strategies in a practical yet comprehensive way. It covers a broad range of ML techniques from linear regression to deep reinforcement learning and demonstrates how to build, backtest, and evaluate a trading strategy driven by model predictions. | github |
- Best-of Machine Learning with Python: This curated list contains 920 awesome open-source projects with a total of 4.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome!
- Homemade Machine Learning: Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained. The purpose of this repository is not to implement machine learning algorithms by using 3rd party library one-liners but rather to practice implementing these algorithms from scratch and get better understanding of the mathematics behind each algorithm. That's why all algorithms implementations are called "homemade" and not intended to be used for production.
| Name | Description | Link(s) |
|---|---|---|
| FixMyResume | Fix your resume using AI, Find out if your resume fits the job you’re applying for. | Webpage - link |
| ACCIO | Instantly Generate Resume Summary, Get a Quick Assessment of Any Resume Based on Job Role | Webpage - link |
| machine-learning-interview | Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io. | github |
- freeCodeCamp: link
| Name | Link(s) |
|---|---|
| Python | webPage |
Brandon Roher Blog: link