ishanyash

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

DTW-Example

Example of DTW algorithm's working.

Error-rates-on-UCR-TS

To compute error rates on UCR time series Data sets and to compare them within. This has 1NN ED, 1NN DTW, 1NN DTW(r),BOSS,SAX,BOSSVS and WEASEL Algorithms.

Indian_liver_patient

The data set consists of the data of liver diseased patients from the Indian subcontinent, and this helps building a ML model using Random Forest and Logistic regression to predict the diseased.

OpenAI_PDF_reader

but this basically provides a way to access PDF(s). This also has some drawbacks for the unpaid version of the openai version of this API. So the code snippet can read the PDFs (Can get the text from Graphs too). Further, it cleans the text by following the classic sentiment analysis way to clean it

SAX-Implementation-on-UCR-TS

Implementing Symbolic Aggregate approXimation to find the error rate and accuracy on the UCR timeseries datasets (https://www.cs.ucr.edu/~eamonn/time_series_data/).

Sensor_SVM

Time series classification using DTW distances as a feature, LIBSVM and WEASEL methods, on the Robosensor data.

Signlearning

Machine learning project made by our team at Hacktech 2019, Caltech. Tracks the pose and orientation of the user's hand and compares it against a database of know signs. Integrating more leap-motion cameras and a user friendly interface! Also, building out the gesture/sign language library!

Time-Series-classification-using-feature-extraction

Using Dynamic time warping distances as features for improved time series classification. We use DTW distances between time series as features and then predict the labels.

UCR-Time-Series-classification

To find the accuracy of the the UCR time series datasets, using kNN algorithm.

ishanyash/SAX-Implementation-on-UCR-TS

Implementing Symbolic Aggregate approXimation to find the error rate and accuracy on the UCR timeseries datasets (https://www.cs.ucr.edu/~eamonn/time_series_data/).

ishanyash/Time-Series-classification-using-feature-extraction

Using Dynamic time warping distances as features for improved time series classification. We use DTW distances between time series as features and then predict the labels.

ishanyash/Signlearning

Machine learning project made by our team at Hacktech 2019, Caltech. Tracks the pose and orientation of the user's hand and compares it against a database of know signs. Integrating more leap-motion cameras and a user friendly interface! Also, building out the gesture/sign language library!

ishanyash/awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

ishanyash/DTW-Example

Example of DTW algorithm's working.

ishanyash/Indian_liver_patient

The data set consists of the data of liver diseased patients from the Indian subcontinent, and this helps building a ML model using Random Forest and Logistic regression to predict the diseased.

ishanyash/OpenAI_PDF_reader

but this basically provides a way to access PDF(s). This also has some drawbacks for the unpaid version of the openai version of this API. So the code snippet can read the PDFs (Can get the text from Graphs too). Further, it cleans the text by following the classic sentiment analysis way to clean it

ishanyash/Text-Analytics

Just a revision and my small experiments in Text Analytics, taught by Warwick Business School.

ishanyash/Advanced-Machine-Learning-Specialization

Advanced Machine Learning Specialization on Coursera

ishanyash/Amazon_Cell_data_review

Text Analytics Group Project using R for WBS Text Analytics coursework.

ishanyash/Artificial-Intelligence-Projects

Collection of Artificial Intelligence projects.

ishanyash/Autoencoders_trial

Training Deep auto encoders and apply them to faces and similar image search.

ishanyash/cloud_basics_test

This is my rough work to learn Cloud Basics

ishanyash/Data_analysis_transgender_issues

ishanyash/Digit_classification

The Notebook will introduce with the Digit classification technique using MNIST Dataset and Tensorflow.

ishanyash/Disaster_tweet_clf

ishanyash/Eye_detection

Eye Detection using openCV

ishanyash/gradhub_backend

Prototype of the DBSchema models that are ready to be integrated with the frontend

ishanyash/HBS_Survey_project

ishanyash/House_pricing

A Walk through of my approach to the famous House pricing problem on Kaggle.

ishanyash/IMDB_TEXTCLASSIFICATION

ishanyash/ishanyash.github.io

ishanyash/ishanyash_test

ishanyash/MNIST_Walkthrough

ishanyash/my_template_project

ishanyash/Opencv_background_elimination

Using OpenCV we will be segregating moving objects using background elimination.

ishanyash/Self_Driving_Car_checkpoint

Using Neural networks we have trained a model to steer the wheel according to the lane the driver is drivinng on.

ishanyash/SmartMeter_London

This repository contains a comprehensive Jupyter notebook dedicated to the preprocessing of smart meter data, laying a robust foundation for subsequent Exploratory Data Analysis (EDA). The notebook is meticulously structured to transform raw data into a format that's conducive to in-depth analysis and insights extraction.

ishanyash/Style_transfer

Basic Style transfer using TensorFlow

ishanyash/Visualization_Intro

A walk through to use the most popular visualization tools in Python.