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Here is the Implementation of Machine Learning algorithms using Python libraries.
Classification Projects (KNN, Decision Trees, SVM, Logistic Regression) Regression (Linear, polynomial, multiple) Clustering (K_means, hierarchical, DBSCAN)Implementation of Regression algorithms from scratch, e.g. gradient descent, MSE.
Supervised Machine-Learning from ScratchWorking on Datasets.
Classification Project: Whether loan is paid off or not Regression Project: TV sales Advertisement Predicting the Price of Houses AutoMobile DataSet Lunar Lander Mars Rover Simulation (Reinforcement Leanring) Find More on My Github ProfileThe following topics are covered in this domain: Exploratory Data Analysis, Feature Extraction, Data Visualization, Regression Algorithms.
Learn MoreVisualization and Extraction of important features from immigirants to Canada Data set. Pandas, Numpy, Seaborn, Plotly, Matplotlib, word clouds, waffle charts, Implementing Dashes.
Learn MoreImplementation of Supervised (Regression, Classification), Unsupervised Machine Learning Algorithms.
Learn MoreA deeper Look at Supervised machine Learning algorithms, implementing each and everything form scratch with interactive visual tools.
Learn MoreA deeper Look at Classification algorithms, implementing each and everything form basic with interactive visual tools. Deep Learning Frameworks TensorFlow, Pytorch used.
Learn MoreA deeper Look at Clustering, Reinforcement Learning and Anomaly Detection with interactive visual tools. e.g. PCA, mars rover simulation.
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