bmanobel's repositories
disentangled-autoencoders
University of Cambridge - Dissertation
awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
anomaliesinoptions
In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
MonteCarloTutorial
Repo to supplement my tutorial on Monte Carlo Simulations and Importance Sampling
Deep-Learning-for-Time-Series-Forecasting
This repository is designed to teach you, step-by-step, how to develop deep learning methods for time series forecasting with concrete and executable examples in Python.
keras-elmo
How to use ELMo embeddings in Keras with Tensorflow Hub
katacoda-scenarios
Katacoda Scenarios
training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
python-ml-course
Curso de Introducción a Machine Learning con Python
EBAD
Analisis Bayesiano de Datos
Hands-On-Natural-Language-Processing-with-Python
This repository is for my students of Udemy. You can find all lecture codes along with mentioned files for reading in here. So, feel free to clone it and if you have any problem just raise a question.
CS231n-2017-Summary
After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.
awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
case-study-credit-data
different classification techniques applied to german_credit_dataset
transfer-learning
Support code for the medium blog on transfer learning. Link to the blog in the Readme file.
Case-study-UK-accidents-2016
Road Safety. Reduce the number of accidents in 2017 based on data from 2016 collected by City of York Council about Road Safety in York (UK)
SparkML
Detailed notes and code to learn machine learning with Apache Spark.
pystatsml
Statistics and Machine Learning in Python
ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
the-elements-of-statistical-learning-notebooks
Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman
BVAE-tf
Disentangled Variational Auto-Encoder in TensorFlow / Keras (Beta-VAE)
ai-projects
Artificial Intelligence projects, documentation and code.
Deteccion_de_anomalias
Detección de Anomalías con Python Pandas
VariationalAutoencoders
Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.
tensorflow-safari-course
Exercises and solutions to accompany my Safari course introducing TensorFlow.
seriestemporales
Compendio de conocimiento sobre series temporales, para la predicción de series temporales con todos los métodos tratados en nuestro laboratorio DICITS.
QGIS_WorkShop
Introduction to QGIS (5 hours)