akshayratnawat

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.

Capstone

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

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.

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.

ReinforcementLearning_MarkovProcess

This project involves analyzing and simulating a Markov Chain and estimating transition matrix for a Reinforcement Learning agent under different policies

akshayratnawat/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.

akshayratnawat/Capstone

akshayratnawat/CommentToxicityPredictor_NLP

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

akshayratnawat/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.

akshayratnawat/Latent_Class_Analysis

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

akshayratnawat/NaturalLanguageProcessingSpecialization

akshayratnawat/PCA_BostonHousingData

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

akshayratnawat/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.

akshayratnawat/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.

akshayratnawat/ReinforcementLearning_MarkovProcess

This project involves analyzing and simulating a Markov Chain and estimating transition matrix for a Reinforcement Learning agent under different policies

akshayratnawat/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.

akshayratnawat/ai8x-training

Model Training for Maxim AI Devices

akshayratnawat/applied-ml

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

akshayratnawat/awesome-deep-rl

A curated list of awesome Deep Reinforcement Learning resources.

akshayratnawat/awesome-rl

Reinforcement learning resources curated

akshayratnawat/awesome-webots

Awesome Webots

akshayratnawat/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

akshayratnawat/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.

akshayratnawat/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

akshayratnawat/ChurnAnalysis

akshayratnawat/CNN_Image_Classifier

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

akshayratnawat/coppelia_robotics

akshayratnawat/general_python_topics

Contains sample python codes for general topics.

akshayratnawat/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

akshayratnawat/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.

akshayratnawat/LinearRegression

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

akshayratnawat/ProgrammingForAnalytics

Course material for an intro to programming class for analytics students

akshayratnawat/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.

akshayratnawat/tensorflow2-crash-course

A quick crash course in understanding the essentials of TensorFlow 2 and the integrated Keras API

akshayratnawat/voxceleb_trainer

In defence of metric learning for speaker recognition