Data transform utility for time series

The goal of the project is to predict chickenpox cases one year ahead based on known history. Methods used: ETS decomposition and SARIMA with statsmodels, LSTM with Keras, MINMAX scaling.

Create Music with Machine Learning!

deep learning: prediction de sentiment associé à un tweet

Using Deep Learning to Categorize Music through Spectrogram Analysis

🚀 Unveiling Stock Market Insights with RNNs: A concise exploration of LSTM and GRU models for stock price prediction, featuring a research paper and Jupyter Notebook. 💹📈

Сентиментальный анализ рынка акции

A computer vision model for Indian Sign Language Recognition

LSTM and all other supporting modules are used to predict the next word based on the previous five words.

📈 Experimenting with possible closing price predicition using automated systems

Dicoding Submission : Machine Learning Terapan

Repo for the Deep Learning Specialization offered by Coursera

Different methods for univariate and multivariate time series forecasting using sklearn and keras.

Contains ML projects

A Music Generating Neural Network using MIDI files and an LSTM neural network implemented with Keras

Minimal Docker container for TesseractOCR

Music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate music sequences.

The goal of this project is to accurately predict the future closing value of a given stock across a given period of time in the future.