A simple python program which predicts the success of a movie based on it's type, actor, actress and director. The program uses iMDB api to get the dataset from iMDB server. To predict it uses Data mining and social media data mining concepts.
Machine learning that just works, for effortless production applications
Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
pywFM pywFM is a Python wrapper for Steffen Rendle's libFM. libFM is a Factorization Machine library: Factorization machines (FM) are a generic approa
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies
Bottleneck Bottleneck is a collection of fast, NaN-aware NumPy array functions written in C. As one example, to check if a np.array has any NaNs using
Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen
Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.
Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM
Implementation of different ML Algorithms from scratch, written in Python 3.x
scikit-fem is a lightweight Python 3.7+ library for performing finite element assembly. Its main purpose is the transformation of bilinear forms into sparse matrices and linear forms into vectors.
cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t
Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers
Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validat
AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems an
torque_model The torque model is a spiritual successor to op-smart-torque, which was a project to train a neural network to control a car's steering f
BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer
Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar
This project shows steps to build an end to end MLOps architecture that covers data prep, model training, realtime and batch inference, build model registry, track lineage of artifacts and model drif
PyHarmonize: Adding harmony lines to recorded melodies in Python About To use this module, the user provides a wav file containing a melody, the key i
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