datasciencebh Goto Github PK

3i005

Files for the course "Statistique et informatique" at Sorbonne Université, 2018--2019.

a-guide-to-machine-learning-in-r

A series of articles to get started into the field of Machine Learning with R language

ai_curriculum

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

amazonsagemakercourse

SageMaker Course Material

aws-machine-learning-specialty

AWS Machine Learning-Specialty- my notes

aws-ml-sagemaker

aws-sagemaker-deploy

Build & Deploy SciKit Learn Machine Learning Model with AWS Sagemaker

car-drive

cortex-license-plate-reader-client

A client to connect to cortex-provisioned infrastructure on AWS to do license plate identification in real time.

customer-churn-prediction

INSAIDINSTRUCTIONS:You are required to come up with the solution of the given business case.Business Context:This case requires trainees to develop a model for predicting customer churn at a fictitious wireless telecom company and use insights from the model to develop an incentive plan for enticing would-be churners to remain with company.Data for the case are available in csv format. The data are a scaled down version of the full database generously donated by an anonymous wireless telephone company. There are still 7043 customers in the database, and 20 potential predictors. Candidates can use whatever method they wish to develop their machine learning model. The data are available inone data file with 7043 rows that combines the calibration and validation customers. “calibration” database consisting of 4000customers and a “validation” database consisting of 3043customers. Each database contained (1) a “churn” variable signifying whether the customer had left the company two months after observation, and (2) a set of 20 potential predictor variables that could be used in a predictive churn model. Following usual model development procedures, the model would be estimated on the calibration data and tested on the validation data.

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

data-science-projects-with-python

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

datasciencetools

Useful Data Science and Machine Learning Tools,Libraries and Packages

deep-learning-youtube

demandforecasting-sagemaker

[Kaggle] Bike Sharing Demand Forecasting using XGBoost. Training and Deploying on SageMaker

dirinfo

Dirinfo

dirinfo_inference

dna-aws-deepar-algorithm-implementation-python

Implementation of AWS DeepAR algorithm using boto3 in sagemaker

docker-course-xgboost

Materials for an online-course - "Practical XGBoost in Python"

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

ds_pyhton

Combine Python with machine learning principles to discover hidden patterns in raw data

dsc

dscience-econtent

end-to-end-time-series

This repository hosts code for my Time Series videos part of playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJd6GrQvhAtpBK

fraud_detection

Tuning XGBoost hyper-parameters with Simulated Annealing

ga_sessions

A Placeholder of all the scripts & notebooks which I'll be using for GA Sessions

gluon-ts

Probabilistic time series modeling in Python

house-prices-advanced-regression-techniques-kaggle

housepriceprediction