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anomaly-detection

Anomaly detection is often referred to as outlier detection, anomaly detection is essentially the method of detection and recognition of anomalous data in any data-based occurrence

basics

📚 Learn ML with clean code, simplified math and illustrative visuals. As you learn, work on interesting projects and share them on https://madewithml.com for the community to discover and learn from!

bert-sentiment

deep_learning_notebooks

A collection of some of my deep learning experiments on NLP. Fork it, improve it :)

dlaicourse

Notebooks for learning deep learning

fastbook

Draft of the fastai book

haberman

Haberman’s data set contains data from the study conducted in University of Chicago’s Billings Hospital between year 1958 to 1970 for the patients who undergone surgery of breast cancer.

hackathons

This repo contains my hackathon solutions

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

is_that_a_duplicate_quora_question

spark-with-python

Fundamentals of Spark with Python (using PySpark), code examples

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.