Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.
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Updated
Jun 6, 2024 - Jupyter Notebook
Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.
📊 Computation and processing of models' parameters
Materiales de las clases prácticas de AID y Aprendizaje Automático
โค้ดประกอบเนื้อหา Python Machine Learning เบื้องต้น
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Implementing PCA on MNIST and then performing GMM clustering. PCA is performed from scratch and done for 32, 64, and 128 components. Clustering performed in 10, 7, and 4 clusters.
A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
Performing K-means clustering on MNIST data from scratch. Instead of using Euclidean distance metric, I have used Cosine Similarity as distance metric. Clustering is done in 10, 7, and 4 clusters for analysis.
Here we have fully implemented a number of algorithms related to machine learning
All Assignments of the course, Statistical Methods in AI at IIITH, Monsoon 2024
Course Material for Artificial Intelligence and Machine Learning - Unit 2 @ Computer Science Dept, Sapienza
This project explores the use of classification algorithms in predicting patient drug use.
Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
Predict the energy consumed by appliances using custom-coded Machine Learning models and Algorithms like PCA, Neural Networks, Lasso, Ridge, and Linear Regression.
This project uses machine learning to predict diabetes and provides explanations through SHAP and PCA, displayed in an intuitive user interface.
This is a remake of my Capstone Project on Image Classification using Scikit-learn and TensorFlow. I initially completed this project as a part of my Data Science diploma studies at Brainstation in June 2023.
Slides, exercises, and exams for my course "Statistical Learning with R" (Ecole Normale Supérieure Paris-Saclay, 2023)
Учебные материалы по курсам связанным с Машинным обучением, которые я читаю в УрФУ. Презентации, блокноты ipynb, ссылки
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