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2017-controverses-groupe-3-court-metrage-video

2017-controverses-groupe-3-court-metrage-video created by GitHub Classroom

advanced-statistical-inference

An introduction to Bayesian machine learning through a collection of notebooks

adversarially-learned-anomaly-detection

ALAD (Proceedings of IEEE ICDM 2018) official code

artificial-neural-networks-for-handwritten-digits-recognition

implementation, training and test of a Neural Network for the Handwritten Digits Recognition problem with different settings of hyperparameters. The dataset used here is The MNIST dataset which was constructed from scanned documents available from the National Institute of Standards and Technology (NIST). Images of digits were taken from a variety of scanned documents, normalized in size and centered.

computer_vision_and_object_recognition

Implementation of visual search using Bags of Visual Words with SIFT detectors. Implementation of Neural Networks for object recognition. Labs and final projects from the corresponding ENS Ulm courses by Jean Ponce, Ivan Laptev, and Cordelia Schmidt

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

datacamp-challenge

datacamp challenge

financial-risk-estimation

Financial risk analysis on a stocks portfolio through the VaR (Value at Risk), using Monte Carlo Simulation and Multiple Linear Regression.

house-prices-prediction

A full-fledged approach to make predictions about the future sale prices of houses.This approach consists in: Descriptive statistics about the data, Data cleaning and pre-processing, Defining a modeling approach to the problem, Build such a statistical model and Validate the outcome of the model.

lectures-labs

Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

music-recommender-system

Song Recommendation System written in Python, applying the collaborative-filtering approach and adopting the ALS model (Alternating Least Squares)

oesth-webapp

openfoodfacts-ai

This is to track all our AI endeavours, and wishlists 🍕 🤖🍼

rf-prediction-problem

Here is a prediction problem using RandomForest with feature transformation attempt and parameter tuning to improve F1&AUC successfully

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

theoretical-guidelines-for-high-dimensional-data-analysis

timeseriesanalysiswithpython

Time Series Analysis with Python