Pinned Repositories
10-k-Filing--Sentiment-analysis-NLP-ML
NLP-10 k report Sentiment Analysis
accel-brain-code
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
personalGPT
personal GPT
spectre
GPU-accelerated Factors analysis library and Backtester
StarTrader
This program trains an agent: StarTrader to trade like a human using a deep reinforcement learning algorithm: deep deterministic policy gradient (DDPG) learning algorithm.
Stock-Market-Analysis
Stock Market Analysis with RNN and Time Series
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
timeseriesAI
Practical Deep Learning for Time Series / Sequential Data library based on fastai v2/ Pytorch
MohitJuneja's Repositories
MohitJuneja/spectre
GPU-accelerated Factors analysis library and Backtester
MohitJuneja/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
MohitJuneja/timeseriesAI
Practical Deep Learning for Time Series / Sequential Data library based on fastai v2/ Pytorch
MohitJuneja/bert-extractive-summarizer
Easy to use extractive text summarization with BERT
MohitJuneja/blog
MohitJuneja/Copycat-abstractive-opinion-summarizer
ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation
MohitJuneja/Credit-Risk-Model
Credit Risk Model on Machine learning and prediction
MohitJuneja/Credit-Risk-Modelling
MohitJuneja/deeplearning-models
A collection of various deep learning architectures, models, and tips
MohitJuneja/fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
MohitJuneja/financial_headline_sentiment
Capstone Project for Udacity Machine Learning Engineering Nanodegree
MohitJuneja/finBERT
Financial Sentiment Analysis with BERT
MohitJuneja/Hands-On-Deep-Learning-for-Finance
Hands-on Deep Learning for Finance published by Packt.
MohitJuneja/MachineLearningStocks
Using python and scikit-learn to make stock predictions
MohitJuneja/MatchSum
Code for ACL 2020 paper: "Extractive Summarization as Text Matching"
MohitJuneja/MBS-default-prediction
A program to take in loan level data and create a model which can predict probability of default
MohitJuneja/mlflow-examples
Basic MLflow examples
MohitJuneja/Multi-News
Large-scale multi-document summarization dataset and code
MohitJuneja/nlp
MohitJuneja/pandas_exercises
Practice your pandas skills!
MohitJuneja/pointer-generator
The pytorch implementation of Get To The Point: Summarization with Pointer-Generator Networks.
MohitJuneja/pointer_summarizer
pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"
MohitJuneja/PreSumm
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders
MohitJuneja/ProFeTorch
Time Series Analysis with Deep Learning.
MohitJuneja/simpletransformers
Transformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
MohitJuneja/text_summurization_abstractive_methods
Multiple implementations for abstractive text summurization , using google colab
MohitJuneja/timeseriesAI1
Practical Deep Learning for Time Series / Sequential Data using fastai1/ Pytorch
MohitJuneja/TitleStylist
Source code for our "TitleStylist" paper at ACL 2020
MohitJuneja/transformer-pointer-generator
A Abstractive Summarization Implementation with Transformer and Pointer-generator
MohitJuneja/WQU-Projects
Projects are developed for implementing the knowledge gained in the courses studied at World Quant University and meeting the requirement of clearing the courses.