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Remarkable performance of Deep Learning Models cann't be achieved without the massive data, this tool can help you to augment your time series data customly.

Human activity recognition, or HAR, is a challenging time series classification task. It involves predicting the movement of a person based on sensor data and traditionally involves deep domain expertise and methods from signal processing to correctly engineer features from the raw data in order... Read more

Modern and future vehicles are complex cyber-physical sys-tems. The connection to their outside environment raises many securityproblems that impact our safety directly. In this work, we propose a DeepCAN intrusion detection system framework. We propose a multivariatetime series representation ... Read more

Through chatbots one can communicate with text or voice interface and get reply through Artificial intelligence. Typically, a chat bot will communicate with a real person. Chat bots are used in applications such as ecommerce customer service, call centres and Internet gaming. Chatbots are program... Read more

implementation of a Deep Kernelized Auto Encoder for learning vectorial representations of mutlivariate time series with missing data.

Yield Prediction Using Deep Learning on Multivariate Time Series Data

Hands-on training labs for Deep Learning in Time Series course by CERTIFAI

A Deep Belief Network for predicting time series in Pytorch.

Mini Projects on Deep Learning including Convolutional Neural Networks, Recurrent Neural Networks, LSTM, GRU, Transfer Learning, Functional API, Wide & Deep Networks, Deep & Cross Networks, Time Series Modelling

This is my thesis work on renewable energy detection which compares state of art models using Machine Learning and Deep Learning adapted from multivariate time series weather data