Pinned Repositories
Ad-Optimization-Reinforcement-Learning
Using UCB and Thompson Sampling to optimize ads click performance
Ad-papers
Papers on Computational Advertising
AdAnalysis
Optimizing ads is one of the most intellectually challenging jobs a data scientist can do. It is a really complex problem given the huge (really really huge) size of the datasets as well as number of features that can be used. Moreover, companies often spend huge amounts of money in ads and a small ad optimization improvement can be worth millions of dollars for the company. The goal of this project is to look at a few ad campaigns and analyze their current performance as well as predict their future performance.
Ads-Analysis
Recommendation system: Identify top 5 ad campaigns out of 40 in the dataset. Provide recommendations to improve the performance
advance-bayesian-modelling-with-PyMC3
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
amss
Learn Bayesian Regression on simulated dataset
awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
awesome-R
A curated list of awesome R packages, frameworks and software.
datasciences's Repositories
datasciences/lifelines
Survival analysis in Python
datasciences/lifetimes
Lifetime value in Python
datasciences/RSPapers
Must-read papers on Recommender System.
datasciences/tf2_course
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
datasciences/python-deepdive
Python Deep Dive Course - Accompanying Materials
datasciences/colab-notebooks
Colab notebooks exploring different Machine Learning topics.
datasciences/tensor-house
A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain
datasciences/probabilisticprogrammingprimer
datasciences/Bayesian_Inference-graphical_models
Bayesian machine learning, Bayesian deep learning, Probabilistic graphical models
datasciences/pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
datasciences/models
Models and examples built with TensorFlow
datasciences/stat453-deep-learning-ss20
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)
datasciences/Predicting-Loans-via-Machine-Learning
Machine learning approaches for predicting loans status (All LendingClub Loans Data; using Logistic Regression, CatBoost, Pymc3)
datasciences/Bios8366
Advanced Statistical Computing at Vanderbilt University Medical Center's Department of Biostatistics
datasciences/resources
PyMC3 educational resources
datasciences/stat479-machine-learning-fs19
Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison
datasciences/brms
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
datasciences/effective-pandas
Source code for my collection of articles on using pandas.
datasciences/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
datasciences/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
datasciences/amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
datasciences/TensorFlowOnSpark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
datasciences/awesome-R
A curated list of awesome R packages, frameworks and software.
datasciences/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.
datasciences/Bayes_Computing_Course
datasciences/bayesian-machine-learning
Notebooks related to Bayesian methods for machine learning
datasciences/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
datasciences/bayesian-multilevel-modelling
datasciences/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
datasciences/bayesian_hierarchical_model
Hierarchical model to estimate average revenues by tee times