akshayratnawat Goto Github PK

ai8x-training

Model Training for Maxim AI Devices

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-deep-rl

A curated list of awesome Deep Reinforcement Learning resources.

awesome-rl

Reinforcement learning resources curated

awesome-webots

Awesome Webots

baggingalgorithm_central-limit-theorem

This project explains why and how the Bagging algorithm is better. Bagged Models have tighter confidence intervals and are less biased in comparison to the full model

baggingalgorithm_centrallimittheorem

This project explains why and how are the Bagged Models better than the Complete Model. Bagged Model parameters have tighter confidence interval and a lower bias.

battle-of-neighbourhoods

Understand similarities and differences between two different boroughs in Toronto and New York respectively. And find the best neighborhoods for office location for Fortune 500 companies.

boostingalgorithms

This project explores the working of various Boosting algorithms and analyzes the results across different algorithms. Algorithms Used are: Random Forest, Ada Boost, Gradient Boost and XG Boost

capstone

churnanalysis

cnn_image_classifier

This project shows how we can create a CNN to build an Image Classifier.

commenttoxicitypredictor_nlp

The model helps in predicting toxicity of Online comments, trained on Wikipedia comments data using Deep Neural Network (GRU+ GLoVe ))

coppelia_robotics

epuck-box-pushing

TUM_ARL_SS16: With its proximity sensors the ePuck robot can estimate the relative position of a small box and learn to push it in a given direction using Reinforcement Learning.

general_python_topics

Contains sample python codes for general topics.

gradientdescent_algorithms

This file explores the working of various Gradient Descent Algorithms to reach a solution. Algorithms used are: Batch Gradient Descent, Mini Batch Gradient Descent, and Stochastic Gradient Descent

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

kmeans-and-gaussian-mixture-classification

The project explores KMeans and Gaussian Mixture Algorithms to classify the Boston Housing Dataset into different groups based on different parameters.

latent_class_analysis

Latent Class Analysis on German Credit Data Set to find the latent variables affecting the credit outcomes and behaviour

leakgan

The codes of paper "Long Text Generation via Adversarial Training with Leaked Information" on AAAI 2018. Text generation using GAN and Hierarchical Reinforcement Learning.

linearregression

Application of simple and multiple linear regression. It also includes RFE and Gradient Descent Method for simple and multiple regression

naturallanguageprocessingspecialization

pca_bostonhousingdata

Using PCA to reduce the dimension of data and for factor Analysis on Boston Housing Data

pca_chiletourismregion_analysis

USe PCA and other segmentation techniques to find the focus areas for the Chilean Government to increase tourism competitiveness based on different city characteristics data.

programmingforanalytics

Course material for an intro to programming class for analytics students

pytorch-learn-reinforcement-learning

A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.

reachingtargetlocation_reinforcementlearning_webots

The objective is to teach robot to find and reach the target object in the minimum number of steps and using the shortest path and avoiding any obstacles such as humans, walls, etc usinf reinforcement learning algorithms.

real_time_intelligent_system_peopledetection_and_counting

This project is on building a real-time intelligent system which involves building and deploying a model to provide real-time model decisions from the real-time data stream.

reinforcement-learning-in-motion

Code repository for my course on the fundamentals of reinforcement learning