This course will introduce you to a very exciting and highly popular Machine Learning. You'll get applied experience in major areas of Machine Learning which include Prediction, Classification, Clustering and Information Retrieval. Learn to analyze large & complex datasets, build systems that adapt and improve over a period of time, and develop smart applications to make predictions from data.
Importance of Python
Describe the basics of the Python programming language
Install Python and write your first program
Use variables and constants to store, retrieve and calculate information
Utilize core programming tools such as functions and loops
Accomplish multi-step tasks like sorting or looping using tuples
Create programs that are able to read and write data from files
Store data as key/value pairs using Python dictionaries
Using Scikit Learn in Machine Learning Techniques like Regression, Classification, Clustering, Recommender Systems
Doing basic project in Python
Select and process the data
Process data using Graphs Library in Python
Creating capstone project on Machine Learning using TensorFlow in Python
Usage of Python Libraries
Live Classes
INTRODUCTION TO COURSE
00:09:14
INTRODUCTION TO ML
00:08:33
DIFFERENCE BETWEEN AI ML DEEP LEARNING
00:04:07
PYTHON LIBRARIES IN MACHINE LEARNING
00:04:51
SUPERVISED AND UNSUPERVISED LEARNING
00:05:46
INTRODUCTION TO MACHINE LEARNING QUIZ
00:00:00
WHAT IS REGRESSION?
00:03:05
REGRESSION MODELS
00:06:35
LINEAR REGRESSION
00:03:54
LINEAR REGRESSION MODELS SLOPES AND INTERCEPT
00:04:55
LINEAR REGRESSION SKLEARN CODING
00:09:38
LINEAR REGRESSION SKLEARN CODE
LINEAR REGRESSION SKLEARN CODE EXPLAINED
00:22:11
LINEAR REGRESSION ERRORS
00:02:33
RSQUARED
00:04:53
MULTIPLE LINEAR REGRESSION
00:04:08
POLYNOMIAL AND NON LINEAR REGRESSION
00:04:00
REGRESSION QUIZ
00:00:00
ABOUT CLASSIFICATION
00:07:06
KNN
00:06:55
WORKING WITH KNN
00:02:38
EVALUATION METRICS
00:03:12
DECISION TREES
00:05:36
SVM
00:07:19
RANDOM FOREST TUTORIAL
00:14:57
CLASSIFICATION QUIZ
00:00:00
WHAT IS CLUSTERING?
00:06:34
CLUSTERING VS CLASSIFICATIONS
00:07:07
KMEANS CLUSTERING
00:08:01
CLUSTERING QUIZ
00:00:00
RECOMMENDER SYSTEMS
00:06:43
CONTENT BASED RECOMMENDER SYSTEMS
00:06:31
COLLABORATIVE FILTERING
00:06:03
RECOMMENDER SYSTEMS QUIZ
00:00:00
PYTHON BEGINNER PROJECT
00:05:00
PROJECT IMPLEMENTATION
00:07:38
PROJECT CODE
PYTHON LIBRARIES INTRODUCTION
00:06:07
PLOTTING 3D PLOTS & LINES
00:06:05
3D PLOTS SURFACE TRIANGULATION
00:07:38
3D PLOT CODE
INTRO TO MACHINE LEARNING
00:03:11
UNDERSTANDING FLOW CHART
00:06:01
TRAINING AND TESTING THE NETWORK WITH TENSORFLOW AND KERAS
00:11:01
Deep Learning with Tensorflow and Keras Code
FINAL PYTHON QUIZ
00:00:00
MACHINE LEARNING ASSIGNMENT
00:00:00
MACHINE LEARNING LIVE PROJECT
00:00:00
BREAST CANCER PREDICTION LOGISTIC REGRESSION
00:43:32
SPAM MAIL PREDICTION
00:33:38
INTRODUCTION TO ML WORKFLOW
00:06:56
MODEL SELECTION
00:11:17
OVERFITTING
00:08:50
UNDERFITTING
00:06:53
BIAS VARIANCE TRADE OFF
00:09:52
DIMENSIONALITY REDUCTION
00:07:47
GRADIENT DECENT
00:05:02
ML Model deployment using Flask
00:11:55
GITHUB TUTORIAL
00:08:11
Lifetime Video Access
Certificate of Completion
Approx. 3 Months to Complete
Live Classes
Quizzes and Assignments
No Prior Experience Required
Top 50 Interview Question
Resume Building
