Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )
Overview
Distributed Evolutionary Algorithms in Python
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30 Days Of Machine Learning Using Pytorch
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Apple-voice-recognition - Machine Learning
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Fourier-Bayesian estimation of stochastic volatility models
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My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data
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ML-powered Loan-Marketer Customer Filtering Engine
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Retrieve annotated intron sequences and classify them as minor (U12-type) or major (U2-type)
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WAGMA-SGD is a decentralized asynchronous SGD for distributed deep learning training based on model averaging.
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An AutoML survey focusing on practical systems.
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DaCeML - Machine learning powered by data-centric parallel programming.
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AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
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Mortality risk prediction for COVID-19 patients using XGBoost models
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Bayesian Additive Regression Trees For Python
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This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch
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Implementation of different ML Algorithms from scratch, written in Python 3.x
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ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
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Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets
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Fast Fourier Transform-accelerated Interpolation-based t-SNE (FIt-SNE)
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