Certificate in Machine Learning for Non-Tech
-- ViewingNowThe Certificate in Machine Learning for Non-Tech is a valuable course designed for professionals seeking to delve into the rapidly growing field of machine learning. This program bridges the gap between tech and non-tech backgrounds, making it accessible and beneficial for a wide range of learners.
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โข Introduction to Machine Learning: Understanding the basics of machine learning, its types, and applications.
โข Data Preprocessing: Cleaning, transforming, and preparing data for machine learning models.
โข Regression Analysis: Learning about simple and multiple linear regression, polynomial regression, and evaluation metrics.
โข Classification Techniques: Studying decision trees, logistic regression, k-nearest neighbors, and other popular classification algorithms.
โข Clustering Methods: Exploring unsupervised learning, including k-means, hierarchical, and density-based clustering.
โข Dimensionality Reduction: Reducing the number of features using techniques like Principal Component Analysis (PCA) and t-SNE.
โข Neural Networks: Getting started with artificial neural networks, including backpropagation, and deep learning concepts.
โข Evaluation Metrics: Assessing model performance using various metrics, such as accuracy, precision, recall, F1 score, and ROC curves.
โข Hyperparameter Tuning: Optimizing model performance by adjusting and fine-tuning hyperparameters.
โข Real-world Applications: Applying machine learning techniques to real-world problems, such as image classification, sentiment analysis, and recommendation systems.
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