Home

Roadmap

Machine Learning Roadmap 2020 (whimsical.com)

Project ideas

Machine Learning Projects - YouTube

Mathematics

The Complete Mathematics of Neural Networks and Deep Learning (youtube.com)

Machine Learning

• MLU-Explainis an education initiative from Amazon designed to teach machine learning theory and practical application.
• Machine Learning University (MLU) 
• Teaching library for machine learning engineers MiniTorch
• Detailed and clear explanation of ML https://distill.pub/
• A work-in-progress to catalog the state of machine learning in Rust: https://www.arewelearningyet.com/

Deep Learning

https://course.fast.ai/

GenAI :

genieincodebottle/generative-ai: Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation. (github.com)

Courses :

Python code for ML , only main implementation and basic idea CS50’s Introduction to Artificial Intelligence with Python 2023 Machine Learning by StatQuest with Josh Starmer

(not prefered) Machine Learning Playlist by Krish Naik Hindi

Machine Learning with Python and Scikit-Learn – Free Code Camp

== Maths == HarvardX: Introduction to Probability | edX UTAustinX: Linear Algebra - Foundations to Frontiers | edX Matrix Algebra for Engineers | Coursera

== ML/ DL ==

• Machine Learning | Coursera
  • Supervised Machine Learning: Regression and Classification - Week 1: Introduction to Machine Learning - Week 1 | Coursera
  • Advanced Learning Algorithms - Neural Networks - Week 1 | Coursera
  • Unsupervised Learning, Recommenders, Reinforcement Learning - Unsupervised learning - Week 1 | Coursera
• Neural Networks: Zero to Hero  
• Deep Learning | Coursera
• Introduction - Hugging Face NLP Course

The spelled-out intro to neural networks and backpropagation: building micrograd (youtube.com)

Deploy Flask Application on Google Cloud:

https://www.youtube.com/watch?v=sqUuofLBfFw

Every Algorithm in ML

Supervised Learning Algorithms:

• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forest
• Gradient Boosting Machines (GBM)
• Support Vector Machines (SVM)
• K-Nearest Neighbors (KNN)
• Naive Bayes
• Neural Networks (Multilayer Perceptron)
• Ensemble Methods (AdaBoost, Bagging)

Semi-Supervised Learning Algorithms:

• Self-Training

• Co-Training

• Label Propagation

Unsupervised Learning Algorithms:

• K-Means Clustering
• Hierarchical Clustering
• DBSCAN
• Gaussian Mixture Models (GMM)
• Self-Organizing Maps (SOM)
• Principal Component Analysis (PCA)
• Independent Component Analysis (ICA)
• Autoencoders

Other Learning Algorithms:

• Ant Colony Optimization
• Genetic Algorithms
• Particle Swarm Optimization
• Bayesian Networks
• Markov Decision Processes

Reinforcement Learning Algorithms:

• Q-Learning
• Deep Q-Networks (DQN)
• Policy Gradient Methods
• Actor-Critic Methods
• Temporal Difference Learning (TD-Learning)

Natural Language Processing (NLP) Specific Algorithms:

• TF-IDF
• Word2Vec
• Doc2Vec
• Sequence Models (RNNS, LSTM, GRU)
• Transformer Models (BERT, GPT)

Harvesting social media sentiment analysis to enhance stock market prediction using deep learning [PeerJ]

https://www.nytimes.com/interactive/2020/11/21/science/artificial-intelligence-fake-people-faces.html

Banana ripeness stage identifications : https://link.springer.com/article/10.1007/s12652-021-03267-w