Predictive Libraries

11 Components & Libraries

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Predictive Libraries

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy: Pyfolio is automatically instal…

Coursera Machine Learning - Python code

This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignments in the course you are instructed to create complete, stand-alone Octav…

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

Retentioneering is a Python library that makes analyzing clickstreams, user paths (trajectories), and event logs much easier, and yields much broader and deeper insights than funnel analysis. You can…

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

It was last updated to a fully running version in late October, 2021. You should refer to the Jupyter Notebooks in this repository rather than the book's source code, which is badly outdated and will…

Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).

Qlik's advanced analytics integration provides a path to making modern data science algorithms accessible to the wider business audience. This project is an attempt to show what's possible. This repo…

HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems

Currently the following machine learning models are supported: The following machine learning models are currently under development: At the moment the following MPC and optimal control problems can …

Predicts Daily NBA Games Using a Logistic Regression Model

Predicts NBA Games Using a Logistic Regression Model in Python The model uses eight factors scraped from stats.nba.com to determine the predicted result of an NBA game. Each stat is adjusted to per 1…

Data-Analyst-Roadmap for Professionals. This roadmap contains 8 Chapters that can be completed in 8 weeks, whether you are a fresher in the field or an experienced professional who wants to transition into Data Analysis.

Data-Analyst-Roadmap for Students and Professionals 1 - Python Programming 2 - Understanding NumPy 3 - Exploratory Data Analysis (EDA) with Pandas 4 - Data Visualization with Matplotlib and Seaborn 5…

A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository.

Analyzing the IRIS dataset with Sci-Pype This notebook shows how to make new predictions with cached IRIS Classifier Models + Analysis housed in redis. This notebook shows how to make new predictions…

This project provides code examples for SAP HANA Predictive and Machine Learning scenarios and is educational content. It covers simple Predictive Analysis Library SQL examples as well as complete SAP HANA design-time “ML scenario”-application content or HANA-ML Python Notebook examples.

This project provides code examples for SAP HANA Predictive and Machine Learning scenarios and is educational content. It covers simple Predictive Analysis Library SQL examples as well as complete SA…

N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)

DL evaluation on N-CMAPSS After that, you should run In addition, we offer the data subsampling to handle 'out-of-memory' issues from the given dataset that use the sampling rate of 1Hz. When you set…

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