Courses
Machine Learning Details
- INTRODUCTION
- CONTROL STATEMENTS
- LOOPS
- STRINGS
- DATA STRUCTURES
- FUNCTIONS
- MODULES
- FILE HANDLING
- EXCEPTION HANDLING
- OOPS
- DATABASE
- REGULAR EXPRESSIONS
- MULTI-THREADING
- NETWORKING
- GUI PROGRAMMING
- NUMPY
- INTRODUCTION
- SERIES
- DATA FRAME
- BASIC FUNCTIONALITY
- DESCRIPTIVE STATISTICS
- READING CSV AND JSON FILES
- HANDLING MISSING DATA
- INTRODUCTION
- PLOTTING DATA
- MATPLOTLIB
- PYPLOT
- SEABORN
- TYPES OF VISUALIZATION
- CHOOSING THE RIGHT CHART
- APPLICATIONS OF ML
- TYPES OF ML
- SUPERVISED VS UNSPERVISED ML
- LIBRARIES SUITABLE FOR ML
- REALTIME PROJECTS
- LINEAR REGRESSION
- NON LINEAR REGRESSION
- MULTI-VARIATE
- MODEL EVALUATION
- LOGISTIC REGRESSION
- DECISION TREE
- RANDOM FOREST
- K-NEAREST NEIGHBOR
- SUPPORT VECTOR MACHINES
- NAIVE BAYES
- MODEL EVALUATION
- K-MEANS CLUSTERING
- HIERARCHICAL CLUSTERING
- DIMENSIONALITY REDUCTION
- PRINCIPAL COMPONENT ANALYSIS
- MODEL EVALUATION
- REINFORCEMENT LEARNING
- GRID SEARCH
- HOW TO SAVE MODEL
- BAGGING VS BOOSTING
- DEEP LEARNING