CODE HEROKU DASHBOARD

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Module 0: Getting Started
Python and Libraries Setup
Module 1: Introduction to Python and Statistics
Introduction to Python Programming Intermediate Python Concepts Python Packages For Data Science Numpy & Matplotlib Stats for Machine Learning Exploratory Data Analysis - 1 Exploratory Data Analysis - 2 Inferential Statistics
Module 2: Data Extraction and Cleaning
Introduction to SQL SQL For Data Science - Part 2 Web Scraping with Python Web Scraping with Python - Part 2 Working with APIs Text Data Cleaning Module 2 Revision and Test
Module 3: Supervised Machine Learning
Introduction to Machine Learning Naive Bayes Classifier Content Based Recommendation Systems Recommendation Systems - Collaborative Filtering Gradient Descent For Machine Learning Logistic Regression
Module 4: Intermediate ML Concepts
SVM - Introduction Digit Recognition with SVM Ensemble Methods, Bagging & Boosting
Neural Networks
Introduction to Neural Networks Neural Networks - Part 2 Introduction to TensorFlow Convolution Neural Networks (CNN) Image Classification with CNN
Unsupervised Learning
Introduction to Unsupervised Learning using K-means Principal Component Analysis (PCA) Face Recognition using PCA
Reinforcement Learning
Inroduction to Reinforcement Learning Reinforcement Learning with OpenAI Gym Building a Crawling Robot with Q-Learning
Capstone Project
Part 1 - Research

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