Python brings an exceptional amount of power and versatility to machine learning environments. The language's simple syntax simplifies data validation and streamlines the scraping, processing, refining, cleaning, arranging and analyzing processes, thereby making collaboration with other programmers less of an obstacle. Its user-friendly syntax and powerful tools like NumPy, pandas, and TensorFlow allow developers to build and deploy complex models with ease, making it an indispensable skill in the field. Read more
Foss : Python for Machine Learning - English
Outline: Installation of Miniconda in Ubuntu OS Creating a conda environment for Machine Learning Activating conda environment for Machine Learning Download MLpackage.txt file Install a..
Outline: Introduction to Nearest Neighbors and K Nearest Neighbor Introduction to KNN classification Explanation about Iris dataset KNN working example using one of the iris feature Imp..
Outline: Introduction to K Nearest Neighbor Regression Various distance metrics used in KNN Importing the necessary libraries Loading the iris dataset Standard scaling of the dataset ..
Outline: About Linear Regression About Simple Linear Regression About Multiple Linear Regression About Evaluation Metrics Splitting the data into training and testing sets Implementing..
Outline: Introduction to Logistic Regression Introduction to Binary classification Introduction to Multi class classification About Purchase prediction Implementing Binary classificatio..
Outline: Implementing Multiclass classification Model Instantiation of Multiclass Classification and Model training Visualize this correlation using a heatmap Split the data into trainin..
Outline: Introduction to Decision Tree Describing the dataset Importing required Libraries Loading the dataset Encoding Categorical Features Splitting the dataset into Training and..
Outline: Introduction to Artificial Neural Networks Introduction to Multi-Layer Perceptron About ANN Architecture Explanation of Neuron Structure Importing necessary libraries Loading ..
Outline: About Support Vector Machine Introduction to Linear SVM Introduction to Non-Linear SVM Explanation of the California Housing dataset Importing necessary libraries Loading the..
Outline: Introduction to K-means Clustering Working of K-means Clustering Description about Silhouette Score Description about the customers dataset Importing required Libraries Loa..
Outline: Introduction to Ensemble Learning Introduction to Random Forest Importing Libraries Loading the dataset Data Preprocessing Train and Test Split Model Instantiation of Random ..