Machine Learning Concepts and Application of ML using Python | Data Science Online Course by Udemy

Development Online Course by Udemy, On Sale Here

Learn core concepts of Machine Learning. Apply ML techniques to real-world problems and develop AI/ML based applications

An excellent training about Data Science

Machine Learning Concepts and Application of ML using Python

Uplatz offers this in-depth course on Machine Learning concepts and implementing machine learning with Python. Objective: Learning basic concepts of various machine learning methods is primary objective of this course. This course specifically make student able to learn mathematical concepts, and algorithms used in machine learning techniques for solving real world problems and developing new applications based on machine learning. Course Outcomes: After completion of this course, student will be able to:1. Apply machine learning techniques on real world problem or to develop AI based application2. Analyze and Implement Regression techniques3. Solve and Implement solution of Classification problem4. Understand and implement Unsupervised learning algorithmsTopicsPython for Machine LearningIntroduction of Python for ML, Python modules for ML, Dataset, Apply Algorithms on datasets, Result Analysis from dataset, Future Scope of ML. Introduction to Machine LearningWhat is Machine Learning, Basic Terminologies of Machine Learning, Applications of ML, different Machine learning techniques, Difference between Data Mining and Predictive Analysis, Tools and Techniques of Machine Learning. Types of Machine LearningSupervised Learning, Unsupervised Learning, Reinforcement Learning. Machine Learning Lifecycle. Supervised Learning: Classification and RegressionClassification: K-Nearest Neighbor, Decision Trees, Regression: Model Representation, Linear Regression. Unsupervised and Reinforcement LearningClustering: K-Means Clustering, Hierarchical clustering, Density-Based Clustering. Detailed Syllabus of Machine Learning Course1. Linear AlgebraBasics of Linear AlgebraApplying Linear Algebra to solve problems2. Python ProgrammingIntroduction to PythonPython data typesPython operatorsAdvanced data typesWriting simple Python programPython conditional statementsPython looping statementsBreak and Continue keywords in PythonFunctions in PythonFunction arguments and Function required argumentsDefault argumentsVariable argumentsBuild-in functionsScope of variablesPython Math modulePython Matplotlib moduleBuilding basic GUIapplicationNumPy basicsFile systemFile system with statementFile system with read and writeRandom module basicsPandas basicsMatplotlib basicsBuilding Age Calculator app3. Machine Learning BasicsGet introduced to Machine Learning basicsMachine Learning basics in detail4. Types of Machine LearningGet introduced to Machine Learning typesTypes of Machine Learning in detail5. Multiple Regression6. KNN AlgorithmKNN introKNNalgorithmIntroduction to Confusion MatrixSplitting dataset using TRAINTESTSPLIT7. Decision TreesIntroduction to Decision TreeDecision Tree algorithms8. Unsupervised LearningIntroduction to Unsupervised LearningUnsupervised Learning algorithmsApplying Unsupervised Learning9. AHCAlgorithm10. K-means ClusteringIntroduction to K-means clusteringK-means clustering algorithms in detail11. DBSCANIntroduction to DBSCAN algorithmUnderstand DBSCANalgorithm in detailDBSCANprogram

Udemy is the leading global marketplace for learning and instruction

By connecting students all over the world to the best instructors, Udemy is helping individuals reach their goals and pursue their dreams.

Study anytime, anywhere.

START HERE