Summary

Here are some of the online courses I have been taking.

Each course contains the source codes alongside with the datasets used. Each course also has some videos that explain the source code as well as the concepts. However, keep in mind that the videos are not meant to teach anything to anyone, they were just recorded so that I could get a better grasp of the material.

All my recorded videos: https://www.youtube.com/playlist?list=PLXpWIYsri-61DqIcYvZKr6soO5vfiRoii

The Machine Learning Toolkit folder contains a well-organized summary of the code that I have been learning during my studies.

Topics separated by course

Machine Learning A-Z Hands-On Python & R In Data Science

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

My course-specific videos: https://www.youtube.com/playlist?list=PLXpWIYsri-6139Qql3FA0B-3I1X4zkO-s

Python

• Scikit-Learn
• TensorFlow
• Numpy
• Pandas
• Matplotlib
• Seaborn

R

• caTools
• caret
• ggplot2
• e1071
• rpart
• ElemStatLearn
• class
• cluster
• arules
• tm
• MASS

Exploratory Data Analysis

Data Preprocessing

• Missing Data
• Class Imbalance
• Feature Engineering
• Categorical Data Encoding
• Feature Scaling

Hyperparameter Tuning

Model Evaluation

Supervised Learning

• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Linear Regression
• Support Vector Regressor
• Decision Tree Regressor
• Random Forest Regressor
• Extreme Gradient Boosting Regressor
• Logistic Regression Classifier
• k-Nearest Neighbors Classifier
• Support Vector Classifier
• Decision Tree Classifier
• Random Forest Classifier
• Extreme Gradient Boosting Classifier
• Naive Bayes

Unsupervised Learning

• k-Means
• Hierarchical Clustering

Reinforcement Learning

• Upper Confidence Bound
• Thompson Sampling

Association Rule Learning

• Apriori
• Eclat

Natural Language Processing

• Bag of Words

Deep Learning

• Deep Feed Forward Neural Network
• Convolutional Neural Network

Dimensionality Reduction

• Feature Selection
  • Filter Method
    • Variance Threshold
    • Chi-Square Test
    • Correlation Threshold
  • Wrapper Method
    • Backward Elimination
    • Recursive Feature Elimination
  • Embedded Method
    • LassoCV
• Feature Extraction
  • Principal Component Analysis
  • Kernel Principal Component Analysis
  • Linear Discriminant Analysis

Python for Data Science and Machine Learning Bootcamp

Course: https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

My course-specific videos: https://www.youtube.com/playlist?list=PLXpWIYsri-6139Qql3FA0B-3I1X4zkO-s

Python

• Scikit-Learn
• TensorFlow
• Numpy
• Pandas
• Matplotlib
• Seaborn
• Cufflinks
• Plotly
• PySpark

Exploratory Data Analysis

Data Preprocessing

• Missing Data
• Class Imbalance
• Feature Engineering
• Categorical Data Encoding
• Feature Scaling

Hyperparameter Tuning

Model Evaluation

Supervised Learning

• Simple Linear Regression
• Multiple Linear Regression
• Logistic Regression
• k-Nearest Neighbors
• Decision Tree
• Random Forest
• Support Vector Machine

Unsupervised Learning

• k-Means
• Principal Component Analysis

Recommender System

• Content Based
• Collaborative Filtering
  • Memory-Based
    • User-Based
    • Item-Based
  • Model-Based

Natural Language Processing

• Bag of Words and TF-IDF

Deep Learning

• Deep Feed Forward Neural Network

Dimensionality Reduction

• Feature Selection
  • Filter Method
    • Variance Threshold
    • Chi-Square Test
    • Correlation Threshold
  • Wrapper Method
    • Backward Elimination
    • Recursive Feature Elimination
  • Embedded Method
    • LassoCV
• Feature Extraction
  • Principal Component Analysis
  • Kernel Principal Component Analysis
  • Linear Discriminant Analysis

Big Data

Spark and Python for Big Data with PySpark

Course: https://www.udemy.com/course/spark-and-python-for-big-data-with-pyspark/

My course-specific videos: https://www.youtube.com/playlist?list=PLXpWIYsri-61tcRzgHYtqZcEqaEpOcbMa

Python

• PySpark

Big Data

Exploratory Data Analysis

Data Preprocessing

• Missing Data
• Categorical Data Encoding
• Feature Scaling

Model Evaluation

Supervised Learning

• Linear Regression
• Logistic Regression
• Decision Tree
• Random Forest

Unsupervised Learning

• k-Means

Recommender System

Natural Language Processing

• Bag of Words and TF-IDF

Spark Streaming

Data Science A-Z Real-Life Data Science Exercises Included

Course: https://www.udemy.com/course/datascience/

My course-specific videos: https://www.youtube.com/playlist?list=PLXpWIYsri-62CcYVQdT73S6FRwlg1E3qG

Data Visualization Tableau

Statistical Package Gretl

• Simple Linear Regression
• Multiple Linear Regression
• Logistic Regression

Data Visualization and Analysis: Microsoft Excel

Extract Transform Load

• Data Cleaning
• Microsoft Visual Studio - SQL Server Integration Services
  • Flat File Source
  • Flat File Destination
  • Conditional Split
  • OLE DB Destination
• Microsoft SQL Server Management Studio
  • Scripts in SQL
  • Stored Procedures in SQL
• Error Handling

SQL

Working with People

• Communication
• Presentations

Deployment of Machine Learning Models

Course: https://www.udemy.com/course/deployment-of-machine-learning-models/

My course-specific videos: https://www.youtube.com/playlist?list=PLXpWIYsri-61nn4Dg-cfkN_30ekZFweDx

Python

• Scikit-Learn
• TensorFlow
• Numpy
• Pandas
• Matplotlib

Data Preprocessing

• Missing Data
• Class Imbalance
• Feature Engineering
• Categorical Data Encoding
• Feature Scaling

Model Evaluation

Supervised Learning

• Lasso

Deep Learning

• Convolutional Neural Network

Machine Learning Pipeline

Research Environment

Production Environment

Machine Learning System Architecture

• Train by batch, predict on the fly, serve via REST API

Production Code Types

• Procedural Programming
• Custom Pipeline
• Scikit-Learn Pipeline

Version Control

• Platform: GitHub

Virtual Environment

• Library: Tox

Versioning

Logging

Testing

• Library: Pytest

Differential Testing

• Library: Pytest

Data Validation

• Library: Marshmallow

Model Deployment via a REST API

• Library: Flask

Packaging

• Libraries: Setuptools, Wheel
• Container: Docker
• Repository: Gemfury

Continuous Integration / Continuous Delivery

• Platform: CircleCI

Deployment Environment

• Platform as a Service
  • Platform: Heroku
    • WSGI HTTP Server: Gunicorn
• Infrastructure as a Service
  • Platform: AWS ECS - AWS ECR
    • Launch Type: EC2 and Fargate

Python and Flask Bootcamp Create Websites using Flask

Course: https://www.udemy.com/course/python-and-flask-bootcamp-create-websites-using-flask/

My course-specific videos: https://www.youtube.com/playlist?list=PLXpWIYsri-62px2Wr_YgZhLWBI5tS9EZ2

Python

HTML

CSS

Bootstrap4

Flask

• Templating: Jinja
• Forms: WTForms
• Object Relational Mapper: Flank-SQLAlchemy
• Database Migration: Flask-Migrate
• User Authentication:
  • Hashing: Bcrypt
  • Hashing: Werkszeug
  • Login: Flask-Login
  • Open Authorization: Flask-Dance
• REST API: Flask-Restful
• Testing: Postman
• API Authorization: Flask-JWT
• Deployment: Heroku
  • WSGI HTTP Server: Gunicorn
• Online Payment Processing: Stripe