scikit-learn-python

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Compilation of R and Python programming codes on the Data Professor YouTube channel.

The practitioner's forecasting library

🔉 👦 👧Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)

Popular collection of practical Python notebooks for machine learning, deep learning, time series, generative AI, and analytics.

A fast, robust library to check for offensive language in strings, dropdown replacement of "profanity-check".

In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features. Learning problems fall into a few categories: supervised lea…

🔉 👦 👧 👩 👨 Speaker identification using voice MFCCs and GMM

ML based Artificial Nose for spice identification using an array of 8 MOS gas sensors (MQ135, TGS series) with a PIC microcontroller. Implements Random Forest (100% accuracy) vs MLP comparison on 8135 sensor readings. IEEE conference paper, 2023.

Recognition of the images with artificial intelligence includes train and tests based on Python.

An end-to-end Machine Learning project that predicts student academic performance using data preprocessing, feature engineering, model training, and a Streamlit-based interactive web application.

Efficient sparse matrix implementation for various "Principal Component Analysis"

Machine learning is the sub-field of Computer Science, that gives Computers the ability to learn without being explicitly programmed (Arthur samuel, American pioneer in the field of Computer gaming and AI , coined the term Machine Learning in 1959, while at IBM )

Classification of MXenes into metals and non-metals based on physical properties

Octopi ML API is a Flask-based backend service hosting a machine learning model trained on over 500 software projects to predict development effort. It exposes RESTful endpoints for real-time effort estimation (in person-hours) and facilitates seamless integration with the Octopi frontend.

skfeaturellm is a Python library that brings the power of Large Language Models (LLMs) to feature engineering for tabular data, wrapped in a familiar scikit-learn–style API.

The complete machine learning roadmap — from-scratch Python implementations, the math explained, tested code, and real projects.

The project scope is a weather forecasting model based on behavioral analysis of the last 33 hours (hour-by-hour forecast) with Random Forest Classifier. The program automatically saves and loads the last trained model for prediction.

A Course from kaggle solved Exercises

Enhancing GPS Positioning Accuracy Using Machine Learning