LinearRegression2 Tvads and CarSales

Last update: Dec 29, 2021

Overview

LinearRegression2_Tvads_and_CarSales

This project infers the insight that how the TV ads for cars and car Sales are being linked with each other. It is linear regression model that provides a linear regression equation or a relationship between the independent variable-number of tv ads and the dependent variable-Number of cars sold.It uses the python Libraries sklearn,statsmodels.api for OLS(Ordiniary Least Square Method) method and add_Constant method,pandas library for creating and fetching data_frame,numpy library,scpiy.

Owner

Ashish Kumar Yadav

GitHub Repository https://github.com/ashishyadav24092000/LinearRegression2_Tvads_and_CarSales

Empyrial is a Python-based open-source quantitative investment library dedicated to financial institutions and retail investors

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

640 Dec 31, 2022

Python module for performing linear regression for data with measurement errors and intrinsic scatter

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

56 Sep 27, 2022

machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service

This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made th

73 Dec 01, 2022

TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery

A powerful and flexible machine learning platform for drug discovery

1.1k Jan 08, 2023

Tools for diffing and merging of Jupyter notebooks.

nbdime provides tools for diffing and merging of Jupyter Notebooks.

2.3k Jan 03, 2023

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o

648 Dec 16, 2022

Python module for data science and machine learning users.

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

1 Nov 23, 2021

Implementation of K-Nearest Neighbors Algorithm Using PySpark

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:

4 Dec 30, 2022

STUMPY is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

2.5k Jan 06, 2023

Bonsai: Gradient Boosted Trees + Bayesian Optimization

Bonsai is a wrapper for the XGBoost and Catboost model training pipelines that leverages Bayesian optimization for computationally efficient hyperparameter tuning.

24 Oct 27, 2022

MLOps pipeline project using Amazon SageMaker Pipelines

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

3 Sep 16, 2022

A simple guide to MLOps through ZenML and its various integrations.

ZenBytes Join our Slack Community and become part of the ZenML family Give the main ZenML repo a GitHub star to show your love ZenBytes is a series of

127 Dec 27, 2022

A Pythonic framework for threat modeling

pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In

644 Dec 20, 2022

Evidently helps analyze machine learning models during validation or production monitoring

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Current

3.1k Jan 07, 2023

Python Machine Learning Jupyter Notebooks (ML website)

Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

2.6k Jan 03, 2023

ml4h is a toolkit for machine learning on clinical data of all kinds including genetics, labs, imaging, clinical notes, and more

65 Dec 20, 2022

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

6.9k Jan 05, 2023