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Machine Learning From Scratch
Published 12/2025
Created by Dr.Ganeshkumar S
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 18 Lectures ( 1h 58m ) | Size: 1 GB [/center]
Master the core ML algorithms by building them from the ground up using pure Python and math
What you'll learn
Understand what Machine Learning is and why it matters
Different types of ML: Supervised, Unsupervised, and Reinforcement Learning
Core Machine Learning Algorithms
Typical ML workflow: Data → Model → Prediction → Evaluation
Requirements
Basic Python Programming
Basic Math Skills
Description
Machine Learning from ScratchThis course is designed to help learners understand machine learning from its core fundamentals, starting from mathematical concepts and gradually translating them into working Python code. Instead of treating machine learning as a black box, this course focuses on how and why algorithms work, making it ideal for students, educators, and professionals who want strong conceptual clarity.You will learn machine learning in a step-by-step, structured manner, beginning with essential mathematics and progressing toward real-world applications. Every algorithm is first explained mathematically and then implemented manually using Python, ensuring deep understanding before using libraries.The course emphasizes application-based learning through carefully designed examples, higher-order assignments, and capstone projects that mirror real industry problems. By the end of the course, learners will be confident in building, analyzing, and evaluating machine learning models independently.What you will learnCore mathematics behind machine learning algorithmsStep-by-step derivation of models from first principlesConverting mathematical equations into Python codeBuilding machine learning algorithms from scratchApplying models to real-world datasetsEvaluating model performance using appropriate metricsCourse FeaturesStep-by-step mathematical approachManual implementation of algorithms using PythonApplication-oriented learning methodologyHigher-order assignments for deeper understandingCourse-end capstone projectsWho this course is forStudents who want strong fundamentals in machine learning
Who this course is for
Students & Beginners, Faculty Members & Educators, Working Professionals & Developers
Machine Learning From Scratch
Published 12/2025
Created by Dr.Ganeshkumar S
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 18 Lectures ( 1h 58m ) | Size: 1 GB [/center]
Master the core ML algorithms by building them from the ground up using pure Python and math
What you'll learn
Understand what Machine Learning is and why it matters
Different types of ML: Supervised, Unsupervised, and Reinforcement Learning
Core Machine Learning Algorithms
Typical ML workflow: Data → Model → Prediction → Evaluation
Requirements
Basic Python Programming
Basic Math Skills
Description
Machine Learning from ScratchThis course is designed to help learners understand machine learning from its core fundamentals, starting from mathematical concepts and gradually translating them into working Python code. Instead of treating machine learning as a black box, this course focuses on how and why algorithms work, making it ideal for students, educators, and professionals who want strong conceptual clarity.You will learn machine learning in a step-by-step, structured manner, beginning with essential mathematics and progressing toward real-world applications. Every algorithm is first explained mathematically and then implemented manually using Python, ensuring deep understanding before using libraries.The course emphasizes application-based learning through carefully designed examples, higher-order assignments, and capstone projects that mirror real industry problems. By the end of the course, learners will be confident in building, analyzing, and evaluating machine learning models independently.What you will learnCore mathematics behind machine learning algorithmsStep-by-step derivation of models from first principlesConverting mathematical equations into Python codeBuilding machine learning algorithms from scratchApplying models to real-world datasetsEvaluating model performance using appropriate metricsCourse FeaturesStep-by-step mathematical approachManual implementation of algorithms using PythonApplication-oriented learning methodologyHigher-order assignments for deeper understandingCourse-end capstone projectsWho this course is forStudents who want strong fundamentals in machine learning
Who this course is for
Students & Beginners, Faculty Members & Educators, Working Professionals & Developers
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