material and notes for my ML workshop, from "almost not a programmer" to "implementing machine learning pipelines"

More resources

1a - Introduction to ML Intro to the workshop, expectations, calibration

1c - from There to Here

2a - ML concepts

2c - Neural networks and Deep learning basics

2d - NLP

3a - Bleeding Edge & Transfer Learning

3c - Recap

3a - Real Data in the Wild

intro to python

pandas + text: preparing horoscopes

pandas: plotting population and CO2

pandas: intro plotting baby names

pandas: sanity checking and plotting

Start to end project: linear regression of California house costs

Start to end classification projects

Start to end: classification on the Titanic

NLP and classification on fake reviews

Advanced classification, dimension reduction, faces, SVM

Basic Neural Nets in Keras

Preprocessing PDFs

Basic NLP

Neural Networks: using fashion

Convolutional Neural Networks, and transfer learning

Convolution

Rock Paper Scissors with CNN

Cats vs. Dogs with CNN

Last minute stuff:

Word Embeddings

Let's try together

Advanced notebooks, to show what's possible

Summarization Trying to get a very, very short version of the bible

Summarizing "sapiens"

Finetuning GPT-2 to generate... horoscopes

Object detection

Detectron for object classification

Using BERT for sentiment analysis

Word Embeddings on BERT

Convolution on Complex Images

Useful material from all over:

CIS 419/519 Applied Machine Learning (University of Pennsylvania)

CS229: Machine Learning (Stanford)