Fourthbrain-ML-Training

This repository contains different learning notebooks for the ML engineer training.

Week 0 Goals

1. Linear Algebra
2. Linear Regression
3. Polynomial Regression

Week 1 Goals

1. Supervised Learning
2. Unsupervised Learning
3. Semi-Supervised Learning
4. Classification
5. Regression

Week 2 Goals

1. Working with unbalanced data
2. Output Metrics and visualization methods
3. Logistic. Regression
4. Support Vector Machines
5. Decision Trees
6. Neuronal Networks
7. Apply data wrangling

Week 3 Goals

1. Clustering
2. PCA
3. Anomaly detection
4. Recommender systems

Week 4 Goals

1. AutoML
2. Zero/One Shot Learning

Week 5 Goals

1. Deep Learning (Neural Networks with Keras)

Week 6 Goals

1. Object detection

Week 7 Goals

1. Semantic Segmentation

Week 9 Goals

1. GANs: pix2pix and cycleGAN