Fundamentals Of Machine Learning by Vasudeva Sunkari
Fundamentals Of Machine Learning by Vasudeva Sunkari
Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With Fundamentals Of Machine Learning by Vasudeva Sunkari, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 929.21 MB | Duration: 1h 37m
Master basics of machine learning from basics and learn NumPy Fundamentals
What you'll learn
Understand the Core Concepts of Machine Learning
Build Machine Learning Models with Python
Apply Essential Machine Learning Algorithms
Develop End-to-End Machine Learning Projects
Requirements
No Prerequisites
Description
Master the fundamentals of Machine Learning and build a strong foundation for a successful career in Artificial Intelligence and Data Science. This beginner-friendly course is designed for students, software developers, data analysts, and professionals who want to understand how machine learning works and apply it to real-world problems using Python.You will begin with the core concepts of machine learning, including different types of learning, data preprocessing, feature engineering, and model evaluation. Through hands-on coding exercises, you will learn to use industry-standard Python libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn to build and evaluate machine learning models.The course covers essential machine learning algorithms, including Linear Regression, Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Naive Bayes, and K-Means Clustering. You will also learn model validation techniques, performance metrics, hyperparameter tuning, and best practices for creating accurate and reliable models.By the end of this course, you will have completed practical, real-world projects that reinforce your understanding of machine learning concepts and prepare you to tackle data-driven challenges confidently. Whether you're planning to advance into Data Science, Artificial Intelligence, or MLOps, this course provides the essential skills and practical experience needed to take the next step in your learning journey.
It is for anyone who wants to learn Machine Learning from basics, then this course is for you!
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