Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera
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Sep 2, 2020 - Python
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Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera
neural-network logistic-regression support-vector-machines coursera-machine-learning principal-component-analysis numpy-exercises anomaly-detection machine-learning-ex1 andrew-ng-course python-ml andrew-ng-machine-learning andrew-ng-ml-course
❄️ 🐳 Awesome tools and libs for AI, Deep Learning, Machine Learning, Computer Vision, Data Science, Data Analytics and Cognitive Computing that are baked in the oven to be Native on Kubernetes and Docker with Python, R, Scala, Java, C#, Go, Julia, C++ etc
docker kubernetes data-science scala big-data ai spark analytics ml cognitive-science pachyderm spark-ml python-ml kubeflow seldon-core kubernetes-ai kubernetes-ml kubernetes-data-science kubernetes-analytics spark-kubernetes
A machine learning library for Python and Rust, for PyTorch, Tensorflow and SKLearn models
machine-learning database artificial-intelligence machine-learning-library artificial-intelligence-framework surreal python-ml surrealdb rust-ml surrealml
🟣 Python Ml interview questions and answers to help you prepare for your next machine learning and data science interview in 2026.
data-science machine-learning interview-practice coding-interviews interview-preparation technical-interview-questions machine-learning-interview python-ml data-science-interview data-scientist-interview software-engineer-interview data-science-interview-questions coding-interview-questions machine-learning-interview-questions ai-interview-questions machine-learning-and-data-science python-ml-interview-questions python-ml-questions python-ml-tech-interview
Collection of Notebooks from 30 Days of ML Challenge
Learn-python is a comprehensive repository designed to cover various aspects of Python learning. It includes examples, tutorials, and exercises to help beginners and developers enhance their Python programming skills. Perfect for anyone looking to start or advance their Python journey.
This repository is a long-term, evolving project focused on implementing Machine Learning algorithms from scratch and with optimized/library-based approaches side by side.
python machine-learning ai deep-learning clustering numpy sklearn machine-learning-algorithms regression python3 artificial-intelligence classification batch-script supervised-machine-learning unsupervised-machine-learning python-ml ml-algorithms dataset-generator
This project aims to forecast inflation rates using machine learning techniques. Leveraging historical economic data on GDP and unemployment rates, the model provides predictions for future inflation trends.
AI-powered Resume Optimization & Job Matching Platform. Analyzes job descriptions, detects ATS keyword gaps, rewrites resume bullet points using DeepSeek V3, and exports print-ready PDFs.
Crops disease detection mainly for tomato plants
❄️ 🐳 Awesome tools and libs for AI, Deep Learning, Machine Learning, Computer Vision, Data Science, Data Analytics and Cognitive Computing that are baked in the oven to be Native on Kubernetes and Docker with Python, R, Scala, Java, C#, Go, Julia, C++, Cognonic, etc.
docker kubernetes data-science machine-learning scala big-data spark artificial-intelligence data-analytics pachyderm cognitive banzai spark-ml python-ml kubeflow seldon-core kubernetes-data-science kubernetes-analytics spark-kubernetes cognonic
GripSync — AI-Powered Gaming Setup Optimization & Hand Tracking Platform (FastAPI + MediaPipe + Next.js)
Machine Learning coursework covering financial distress classification and diabetes progression regression, with full Jupyter notebooks and reports.
python machine-learning numpy scikit-learn jupyter-notebook ml pandas data-visualization hyperparameter-optimization data-analysis confusion-matrix gaussian-processes f1-score kfold-cross-validation python-ml bankruptcy-prediction diabetes-prediction shap randomizedsearchcv
This repository contains a complete, runnable example showing how Customer Success teams can use Logistic Regression to predict churn probability and act early.
machine-learning ml logistic-regression predictive-analytics customer-success churn-prediction python-ml customer-churn decision-ai
This repository explores statistical and machine learning methods for classification and function approximation. It covers k-NN, Decision Trees, Information Theory, and Convexity, with Python implementations, theoretical explanations, model comparisons, and visualizations, making it a valuable resource for ML research and applications.
data-science machine-learning text-classification statistical-methods data-visualization supervised-learning classification data-preprocessing decision-trees feature-engineering predictive-modeling countvectorizer k-nearest-neighbors climate-data-analysis python-ml
Stock predictions via ML - live long and prosper
Analyse et Prédiction des Prix de l'Immobilier en Californie
This workspace contains a trained MobileNetV2 model for bird-species classification, the notebooks used to train and test it, and the dataset layout used for training/validation/testing.
machine-learning computer-vision deep-learning cnn image-classification python-ml huggingface bird-classification
Simple spam filter for Python and Brython.
machine-learning ai artificial-intelligence spam-detection python-ml spamfilter python-ai spam-detector spam-cleaner
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