As I ventured into the robotics industry as Software Test & Automation Engineering, I realized that becoming a more robust Robotics Software Engineer meant being able to implement Deep Reinforcement Learning (DRL) into self-developed projects involving hardware and algorithmns (path planning, computer vision, etc). For this dream to become a reality however, I understood this meant being able to grasp the precursors of Machine Learning and Deep Learning.

This repository serves to be a personal and communal benchmark detailing how to progress as a self-learner if curious about following this path as an RSE. I grew inspired by the embedded link on this repo, 'Machine Learning A-Z' by Udemy. I give props to them for the motivation and as the resource I used upon my initial journey debuting February 2024.

Please feel free to merge a PR or reccomendation through comments below. Any advice is always appreciated! :)

• Missing Data
• Categorical Data
• Template For Preprocessing Data (General Steps)

• Simple Linear Regression
• Multiple Linear Regression
• Polynomial regression
• Support Vector Regression
• Decision Tree Regression
• Random Forest Regression
• Evaluating Regression Model
• Regularisation Methods

• Logistic Regression
• K-Nearest Neighbors (K-NN)
• Support Vector Machine (SVM)
• Kernel SVM
• Naive Bayes
• Decision Tree Classification
• Random Forest Classification
• Evaluating Classification Model

• K-Means Clustering
• Hierarchical Clustering

• Apriori
• Eclat

• Upper Confidence Bound (UCB)
• Thompson Sampling
• Q-Learning

• Natural Language Processing
• Decision Tree
• Random Forest
• Max Entropy

• Artificial Neural Networks(ANN)
• Convolutional Neural Netwroks(CNN)
• Recurrent Neural Networks(RNN)

• Principal Component Analysis
• Linear Discriminant Analysis
• Kernel PCA

• Model Selection
• XGBoost

• Similar Movies
• Item Based Collabrative Filtering

• Keras-RNN -Keras-CNN

(Please View in SubBranches)

• Handwriting Recognition
• Predict Political Party
• Fire Detection Project

https://www.udemy.com/course/machinelearning/