rahulraghatate Goto Github PK

ads-click-prediction

To boost the income through ad clicks, it is imperative to understand the significance of the factors affecting ad clicks. After mining through data logs provided by Outbrain,we formulated new learning problem in content ranking based on past clickthrough data to predict which pieces of content (ads) likely to be clicked by global users automatically.We used classification models like Naive Bayes, SVM, Random Forest and Stochastic Gradient Descent algorithms for learning parameterized orderings.

aipnd

Code and associated files for the AI Programming with Python Nanodegree Program

ansible

automatic-fare-collection-system-using-near-field-communication

awesome-interaction-aware-trajectory-prediction

A selection of state-of-the-art research materials on trajectory prediction

classes

All class material

code-challenge

Coding challenge

cule

CuLE: A CUDA port of the Atari Learning Environment (ALE)

data-science-blogs

A curated list of data science blogs

deep-learning

Course: Deep Learning

deeprl-agents

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

deepspeech

A TensorFlow implementation of Baidu's DeepSpeech architecture

exploratory-data-analysis

factors-affecting-ghg-emissions-in-us

Data Modeling and Analysis Project in SAS

housing-sale-price-prediction

"Buying a house is a stressful thing." We built a model to predict the prices of residential homes in Ames, Iowa, using advanced regression techniques. This model will provide buyers with a rough estimate of what the houses are actually worth. We first analyzed the data to find trends. Then dimensionality reduction was performed on the dataset using PCA algorithm and feature selection module in sklearn package for python 3.5. The final house prices are predicted using linear regression models like Ridge and Lasso. We also utilised advanced regression techniques like gradient boosting using XGBoost library in python 3.5.

image-quantization-using-k-means-algorithm

jobtitle_to_function_mapping_challenge

Job_Portal/HR analytics based on job_titles for exploring major Job Functions, Categories, Levels and utilize the results to improvise job portal granularity and outreach.

lending-club-loan-data-analysis

Exploratory Data Analysis carried out as part of academic project for STAT-S670 (EDA) course. Project includes data engineering, feature selection using carat package, Random Forest, Correlation test, etc. , default rate analysis and interest rate automation modeling using linear regression and many more.

machine-learning

ML Algorithms from scratch

machinelearningroguelike

A small Roguelike game that uses Machine Learning to power its entities. Originally used in talks by Ciro & Alessia.

manhattan-crime-analysis

manhattan-properties-sale-analysis

ml-simplest-scenario

The simplest Unity ML Agents scenario I could think of

modular_rl

Implementation of TRPO and related algorithms

monthly-challenges

Repository containing monthly challenges in the field of quantum computing.

ppol

PPOL is a crowd simulator based on Unity's ML Agents and using PPO Reinforcement Learning Algorithm

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

predictive-analysis-model-for-breast-cancer-diagnosis

programs

python-machine-learning-cookbook

Code files for Python-Machine-Learning-Cookbook