Machine Learning Tutorials and Articles
In this repository, I'm uploading code, notebooks and notebooks from my personal blog : https://maelfabien.github.io/ . Don't hesitate to โญ the repo if you enjoy my work ! New articles are being published weekly !
First of all, if you're not familiar with the key concepts of machine learrning, make sure to check this first article :
https://maelfabien.github.io/machinelearning/ml_base/
The repository is organized the following way :
articles and tutorials are posted by category
there is a link to the article in question with the read time specified
the is a link to the code folder for each article
You would like to work on an article with me ? Or you would like me to work on a specific topic ? Feel free to reach out ! ([email protected] )
Machine Learning Cheatsheet :
Supervised Learning
Unsupervised Learning
Article Title
Read Time
Article
Code Folder
The linear regression model (1/2)
14mn
here
here
The linear regression model (3/2)
10mn
here
here
Basics of Statistical Hypothesis Testing
5mn
here
---
The Logistic Regression
4mn
here
here
Statistics in Matlab
4mn
here
---
Article Title
Read Time
Article
Code Folder
The Basics of Machine Learning
4mn
here
---
Bayes Classifier
1mn
here
---
Linear Discriminant Analysis
1mn
here
---
Adaboost and Boosting
7mn
here
here
Gradient Boosting Regression
6mn
here
here
Gradient Boosting Classification
3mn
here
---
Large Scale Kernel Methods for SVM
9mn
here
here
Article Title
Read Time
Article
Code Folder
A full guide to Face, Mouth and Eyes Real Time detection
16mn
here
here
How to use OpenPose on MacOS ?
3mn
here
---
Introduction to Computer Vision
1mn
here
---
Image Filtering and Image Gradients
5mn
here
here
Advanced Filtering and Image Transformation
5mn
here
---
Image Features, Panorama, Matching
5mn
here
---
Article Title
Read Time
Article
Code Folder
Text Pre-Processing
7mn
here
---
Text Embedding with BoW and Tf-Idf
6mn
here
---
Text Embedding with Word2Vec
3mn
here
---
Article Title
Read Time
Article
Code Folder
Introduction to Time Series
4mn
here
here
Key concepts of Time Series
4mn
here
here
Article Title
Read Time
Article
Code Folder
Markov Chains
9mn
here
here
Hidden Markov Models
6mn
here
---
Article Title
Read Time
Article
Code Folder
Introduction to Graph Mining
5mn
here
here
Graph Analysis
4mn
here
here
Graph Algorithms
11mn
here
here
Graph Learning
8mn
here
here
Article Title
Read Time
Article
Code Folder
GridSearch vs. Randomized Search
6mn
here
---
AutoML with h2o
6mn
here
---
Bayesian Hyperparameter Optimization
7mn
here
here
Article Title
Read Time
Article
Code Folder
Introduction to Data Viz
12mn
here
---
Interactive graphs in Python with Altair
5mn
here
here
Dynamic plots with BQ-Plot
---
---
here
Article Title
Read Time
Article
Code Folder
Introduction to Online Learning
5mn
here
---
Linear Classification
1mn
here
---
Article Title
Read Time
Article
Code Folder
The Rosenbaltt's Perceptron
3mn
here
here
Multilayer Perceptron (MLP)
5mn
here
here
Regularization Techniques
1mn
here
---
Convolutional Neural Network
2mn
here
---
Article Title
Read Time
Article
Code Folder
Inception Architecture in Keras
2mn
here
here
Build an autoencoder using Keras functional API
5mn
here
---
XCeption Architecture
5mn
here
here
GANs on the MNIST dataset
---
---
here
Two general articles :
Understanding Computer Components (6mn read)
https://maelfabien.github.io/bigdata/comp_components/
Useful Bash commands (1mn read)
https://maelfabien.github.io/bigdata/Terminal/
Article Title
Read Time
Article
Introduction to Hadoop
4mn
here
MapReduce
3mn
here
HDFS
2mn
here
VMs in Virtual Box
1mn
here
Hadoop with the HortonWorks Sandbox
2mn
here
Load and move files to HDFS
2mn
here
Launch a MapReduce Job
2mn
here
MapReduce Jobs in Python
3mn
here
MapReduce Job in Python locally
1mn
here
Article Title
Read Time
Article
Introduction to Spark
6mn
here
Install Spark-Scala and PySpark
1mn
here
Discover Spark-Scala
2mn
here
Article Title
Read Time
Article
Big (Open) Data, the GDelt project
2mn
here
Install Zeppelin locally
1mn
here
Run Zeppelin on AWS EMR
4mn
here
Work with S3 buckets
1mn
here
Launch and access AWS EC2 instances
2mn
here
Install Apache Cassandra on EC2 Cluster
2mn
here
Install Zookeeper on EC2 instances
3mn
here
Build an ETL in Scala
3mn
here
Move Scala Dataframes to Cassandra
2mn
here
Move Scala Dataframes to Cassandra
2mn
here
Article Title
Read Time
Article
AWS Cloud Concepts
2mn
here
AWS Core Services
1mn
here
Article Title
Read Time
Article
TPU Survival Guide on Colab
8mn
here
Store files on Google Cloud and Colab
1mn
here
Article Title
Read Time
Article
Introduction to ElasticStack
1mn
here
Getting Started with ElasticSearch and Kibana
7mn
here
Install and run Kibana locally
1mn
here
Working with DevTools in ElasticSearch
9mn
here
Working with DevTools in ElasticSearch
9mn
here
Article Title
Read Time
Article
Introduction to Graph Databases
1mn
here
A day at Neo4J GraphTour
7mn
here
Boosting and Adaboost clearly explained : https://towardsdatascience.com/boosting-and-adaboost-clearly-explained-856e21152d3e
A guide to Face Detection in Python : https://towardsdatascience.com/a-guide-to-face-detection-in-python-3eab0f6b9fc1
Markov Chains and HMMs : https://towardsdatascience.com/markov-chains-and-hmms-ceaf2c854788
Stay tuned :)