Philippe Yeonathan Bouaziz's repositories
docs
Source repo for Docker's Documentation
mslearn-tailspin-spacegame-web
Code used in Microsoft Learn modules to support Azure DevOps
python-sample-vscode-flask-tutorial
Sample code for the Flask tutorial in the VS Code documentation
Artificial-Neural-Networks-with-Jupyter
Artificial Neural Networks - Gradient descent, BFGS, Regularization with Jupyter notebook
Best_AutoML_Tools_2021
A collection of the best autoML tools with python codes.
ml-basics
Exercise notebooks for Machine Learning modules on Microsoft Learn
mslearn-dp100
Lab files for Azure Machine Learning exercises
Deep_Learning_Bootcamp
All the learning material for deep learning bootcamp can be found in this repository
ML-for-beginners-Best-01-KNN
A machine learning notebook on VScode for beginners using the KNN algo with IRIS dataset
Reactors
Content for Microsoft Reactor Workshops
My-WiMLDS-Minneapolis-Talks
Women in Machine Learning and Data science presentations and discussion materials
python
Jupyter notebooks and datasets for the interesting pandas/python/data science video series.
mslearn-aml-labs
Azure Machine Learning Lab Notebooks
ms-learn-ml-crash-course-python
Code samples for the ML Crash Course learning path.
House-Prices-Advanced-Regression-Techniques
Predict sales prices and practice feature engineering, RFs, and gradient boosting
Tow-sigma-rental-list
Finding the perfect place to call your new home should be more than browsing through endless listings. RentHop makes apartment search smarter by using data to sort rental listings by quality. But while looking for the perfect apartment is difficult enough, structuring and making sense of all available real estate data programmatically is even harder. Two Sigma and RentHop, a portfolio company of Two Sigma Ventures, invite Kagglers to unleash their creative engines to uncover business value in this unique recruiting competition. Two Sigma invites you to apply your talents in this recruiting competition featuring rental listing data from RentHop. Kagglers will predict the number of inquiries a new listing receives based on the listing’s creation date and other features. Doing so will help RentHop better handle fraud control, identify potential listing quality issues, and allow owners and agents to better understand renters’ needs and preferences. Two Sigma has been at the forefront of applying technology and data science to financial forecasts. While their pioneering advances in big data, AI, and machine learning in the financial world have been pushing the industry forward, as with all other scientific progress, they are driven to make continual progress. This challenge is an opportunity for competitors to gain a sneak peek into Two Sigma's data science work outside of finance.
Principles-of-Machine-Learning-R
Principles of Machine Learning R
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.
ms-learn-ml-crash-course-R
Code samples for the ML Crash Course learning path.
challenge-hackerrank30
Playing with HackerRank 30 Challenge using Clojure, Java, Python, C++, and JavaScript
vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Principles-of-Machine-Learning-Python
Principles of Machine Learning Python
DSN-Project
A Machine Learning Prediction Algorithm
jupyterlab-demo
Demonstrations of JupyterLab
hello-world
tutorial 01