LSTM-RNN Tutorial with LSTM and RNN Tutorial with Demo with Demo Projects such as Stock/Bitcoin Time Series Prediction, Sentiment Analysis, Music Generation using Keras-Tensorflow

Bitcoin price prediction algorithm using bayesian regression techniques

A project of using machine learning model (tree-based) to predict short-term instrument price up or down in high frequency trading.

Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach: A novel algorithmic trading model CNN-TA using a 2-D convolutional neural network based on image processing properties.

ApnaAnaaj aims to solve crop value prediction problem in an efficient way to ensure the guaranteed benefits to the poor farmers. The team decided to use Machine Learning techniques on various data to came out with better solution. This solution uses Decision Tree Regression technique to predict the crop value using the data trained from authenti…

Machine learning regression algorithm on cryptocurrency stock price for the next 30 days.

A Deep Neural-Network based (Deep MLP) Stock Trading System based on Evolutionary (Genetic Algorithm) Optimized Technical Analysis Parameters (using Apache Spark MLlib)

Price Prediction Case Study predicting the Bitcoin price and the Google stock price using Deep Learning, RNN with LSTM layers with TensorFlow and Keras in Python. (Includes: Data, Case Study Paper, Code)

A Fund Price Prediction Framework (LSTM-based, web scraping included) 天天基金网爬虫+基金预测

Conversion of the time series values to 2-D stock bar chart images and prediction using CNN (using Keras-Tensorflow)

📈 Bitcoin bull run peak prediction project (price and date)

Harvard CS109: A predictive model for electricity prices in the midwest, and more specifically, the prices of nodes where nuclear plants are located

Deep learning for price movement prediction using high frequency limit order data

Predicting different market prices using Deep Learning and Recurrent Neural Networks

A new stock trading and prediction model based on a MLP neural network utilizing technical analysis indicator values as features (using Apache Spark MLlib)

Build Deep Neural Network model in Keras and deploy a REST API to production with Flask on Google App Engine

An S&P500 Stock Index Movement Predictor built with Machine Learning models

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions vali…

TensorFlow implementation of Z. Hu et al. "Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction", WSDM 2018

🚗 Solving the problem of predicting the price of a used car using Sklearn's supervised machine learning techniques.