This machine learning model was developed for "House Prices - Advanced Regression Techniques" competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
Cross validation phases are given as comment with their results. They can be uncommented and tested again.
Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning
MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic p
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn
pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-
06.demand-electricity Predict the demand for electricity (R) - FRENCH Prédisez la demande en électricité Prérequis Pour effectuer ce projet, vous devr
Logistic_Regression_Model A logistic regression model for health insurance purchasing prediction This code is using these packages, so please make sur
[Book-2021] Practical MLOps O'Reilly Book
dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin
The Emergence of Individuality
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality wit
Book-Item-Based-Collaborative-Filtering Collaborative filtering methods are used
Py-boost: a research tool for exploring GBDTs Modern gradient boosting toolkits are very complex and are written in low-level programming languages. A
Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in
KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https:
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learn
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