12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
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Nov 7, 2026 - Jupyter Notebook
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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
python education data-science machine-learning r scikit-learn machine-learning-algorithms ml machinelearning machinelearning-python scikit-learn-python microsoft-for-beginners
Compilation of R and Python programming codes on the Data Professor YouTube channel.
python data-science machine-learning r shiny scikit-learn exploratory-data-analysis pandas datascience machinelearning python-data-science data-science-python scikit-learn-python streamlit dataprofessor data-professor
The practitioner's forecasting library
python data-science machine-learning deep-learning time-series scikit-learn keras pandas recurrent-neural-networks lstm forecasting easy-to-use vecm auto-ml msis scikit-learn-python mase smape
🔉 👦 👧Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)
data-science machine-learning scikit-learn voice speech gaussian-mixture-models signal gender-recognition gender gmm mfcc speaker gender-classification vocal gender-recognition-by-voice gender-detection mel-frequencies scikit-learn-python
Popular collection of practical Python notebooks for machine learning, deep learning, time series, generative AI, and analytics.
python twitter-bot data-science machine-learning reinforcement-learning deep-learning time-series neural-network recurrent-neural-networks feature-selection openai neural-networks stock-price-prediction churn-prediction keras-tensorflow stock-market-prediction time-series-prediction time-series-forecasting scikit-learn-python openai-api
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…
python machine-learning reinforcement-learning vector scikit-learn sklearn machine-learning-algorithms scikit-image regression prediction consists supervised-learning classification semi-supervised-learning python-3 unsupervised-learning scikit-model scikit-learn-api scikit-learn-python
🔉 👦 👧 👩 👨 Speaker identification using voice MFCCs and GMM
machine-learning scikit-learn voice speech gaussian-mixture-models signal gmm mfcc speaker-recognition vocal mel-frequencies speaker-identification mel-frequency-cepstral-coefficients scikit-learn-python
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.
iot machine-learning python3 machine-learning-models random-forest-classifier mlp-classifier scikit-learn-python electronic-nose gas-sensors pattern-recognition-and-machine-learning artificial-nose spice-identification
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.
python machine-learning linear-regression scikit-learn machine-learning-algorithms regression machinelearning scikitlearn-machine-learning predictor scikit-learn-python
Recognition of the images with artificial intelligence includes train and tests based on Python.
python opencv recognition numpy scikit-learn sklearn image-processing artificial-intelligence scipy image-processing-library matplotlib pyparsing opencv-python artificial-intelligence-algorithms image-procesing recognition-color scikit-learn-python image-processing-python recognition-py
Efficient sparse matrix implementation for various "Principal Component Analysis"
python pca cca svd sparse-matrix principal-component-analysis ca correspondence-analysis canonical-correlation-analysis scikit-learn-python
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 )
python tensorflow linear-regression supervised-learning logistic-regression clustering-algorithm knearest-neighbor-algorithm classification-algorithm unsupervised-machine-learning scikit-learn-python
Classification of MXenes into metals and non-metals based on physical properties
machine-learning deep-learning neural-network random-forest physics scikit-learn sklearn machine-learning-algorithms logistic-regression machinelearning atoms decision-trees molecules scikitlearn-machine-learning atomic-physics sklearn-classify knn-classifier sklearn-library machinelearning-python scikit-learn-python
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.
Serious AI forensic investigation workstation for tabular datasets: detects target leakage, structural corruption, and statistical anomalies with reproducible evidence and local AI.
scikit-learn-python anomaly-detection-algorithm audit-trails data-profiling-utility data-leakage-prevention
AI-powered Smart Water Leak Detection system using Machine Learning and IoT sensor data. Includes a Streamlit dashboard for real-time leak prediction, geo-visualization, batch analysis, and AI-driven insights.
python machine-learning random-forest jupyter-notebook data-visualization logistic-regression svm-model water-management leak-detection decison-trees scikit-learn-python streamlit ai-assistant pipeline-monitoring
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 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.
weather ai scikit-learn artificial-intelligence weather-information weather-forecast weather-conditions scikit artificial-intelligence-algorithms scikitlearn-machine-learning artificialintelligence artificial-intelligence-projects scikit-learn-python scikitlearn
The complete machine learning roadmap — from-scratch Python implementations, the math explained, tested code, and real projects.
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