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)

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

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.

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 )

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.

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