machinelearning-python

12 weeks, 25 lessons, 50 quizzes, classic Machine Learning for all

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

Machine Learning Concepts with Concepts

Plant Disease Detector Web Application

Tutorial Series (60 hour course): Essentials of computer vision

another custom data science template via cookiecutter

I will update this repository to learn Machine learning with python with statistics content and materials

Stress classifier with AutoML

Indian license plate detection and character extraction using deep learning and raspberry pi.

Python code source for features selection 👨‍🔬 series on medium website. 📰

Flutter App Build for the machine Learning model which shows sentiments of instagram user by analysing their captions

The accompanying code for the book "Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits". A practical guide to implementing supervised and unsupervised machine learning algorithms in Python by Tarek Amr

Edge Computer Vision Course

A simple implementation of a portion of GCN (Kipf & Welling) that can handle graph classification.

Python codes from tutorials on the Data Professor YouTube channel

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

ByteHub: making feature stores simple

Discord bot for coronavirus (COVID-19) , With Ai [Machine learning algorithms] integrated into it

Social Distancing and Face Mask Detection using TensorFlow. Install all required Libraries and GPU drivers as well. Refer to README.md or REPORT for know to installation requirement

Machine Learning (Easy to Hard step by step)

📊 Easily apply audio-related machine learning models trained on the AudioSet dataset (527+ models/classes).

Draw in the air with your favorite pointer

Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discrete variables using various techniques depending on the feature. Checked for missing values and cleaned the data. Built the probability of default model using Logistic Regression. Visualized all the results. Computed Weight of Evidence and price elasticities.

Machine learning notes that make your reading easy

Automatic Machine Learning Model Creation with GUI and Python.

`mllint` is a command-line utility to evaluate the technical quality of Machine Learning (ML) projects by means of static analysis of the project's repository.

This is a repository built by the community for the community.