829 Open source projects that are alternatives of or similar to bitcoin-prediction

I will update this repository to learn Machine learning with python with statistics content and materials

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

PyTorch tutorial for learners

My implementation of "Hierarchical Attention Networks for Document Classification" in Keras

Matlab library for gradient descent algorithms: Version 1.0.1

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

A PureScript, browser-based implementation of simple linear regression.

Machine Learning Concepts with Concepts

AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics

Using LSTM network for time series forecasting

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

How to build RNNs and LSTMs from scratch with NumPy.

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

Basic Machine Learning implementation with python

基于机器学习和OCR的车牌识别系统 @fujunhao

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

Anomaly detection for temporal data using LSTMs

Python code for common Machine Learning Algorithms

Machine Learning Lectures at the European Space Agency (ESA) in 2018

My GitHub blog: things you might be interested, and probably not...

In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays and oil prices.

gesture recognition toolkit

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

Application of machine learning to the Coinbase (GDAX) orderbook

Image Captioning: Implementing the Neural Image Caption Generator with python

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

THEANO-KALDI-RNNs is a project implementing various Recurrent Neural Networks (RNNs) for RNN-HMM speech recognition. The Theano Code is coupled with the Kaldi decoder.

A random forest

A curated list of dedicated resources and applications

OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

100 Days of ML Coding

Plain python implementations of basic machine learning algorithms

A simple machine learning framework written in Swift 🤖

For recognising hand gestures using RNN and LSTM... Implementation in TensorFlow

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

Launch machine learning models into production using flask, docker etc.

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

A day to day plan for this challenge. Covers both theoritical and practical aspects

Text Classification Algorithms: A Survey

Aulas da Escola de Inteligência Artificial de São Paulo

Machine Learning algorithms coded from scratch

Heart Disease prediction using 5 algorithms

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

This repository contains the code for a conference paper "Predicting the football match winner using LSTM model of Recurrent Neural Networks" that we wrote

Python implementation of Andrew Ng's ML course projects

📃 **Unofficial** PyTorch Implementation of DA-RNN (arXiv:1704.02971)

List of papers, code and experiments using deep learning for time series forecasting

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

Automatic trading bot (WIP)

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.