Created By: Team InventModel
Machine Learning(ML) Training
A.1 Introduction to python
A.2 History of python
A.3 Features of python
A.4 Comparison to other languages
A.5 IDLE setup
A.6 Your very first python implementation
Module B: Tokens
B.1 Tokens & its types
B.2 keywords
B.3 Identifiers & it’s constraints
B.4 Literals
B.5 Operators
B.6 Delimiters
B.7 Comments
Module C: Variables
C.1 Python working
C.2 Variables and data types (integers, floats, strings, Booleans)
C.3 Difference between identifiers and variables
C.4 Basic operations
Exercise
Module D: Data Types in Detail
D.1 Numbers
D.2 Strings
D.3 List
D.4 Tuples
D.5 Dictionary
Exercise
Module E: Decision Making
E.1 Introduction
E.2 Syntax (Keywords and Identifiers, Statements, Expressions)
E.3 Decision making (if, else, else if)
Exercises
Module F: Loops
F.1 Loops (for, while)
F.2 Control flow statements (break, pass, and continue)
Exercises
Module G: Functions
G.1 Introduction
G.2 Calling a function
G.3 Arguments
G.4 Types of functions (built in, user defined)
G.5 Scope of variable
G.6 Higher order functions (passing function to function)
G.7 Single line function (lambda function)
Exercises
Module H: Packages & Modules
H.1 Modules and Packages
H.2 Importing modules
H.3 user defined modules
H.4 dir() function
Exercises
Module I: Exceptional Handling
I.1 Errors and its types
I.2 Handling errors
I.3 try, except handling
I.4 raise & assert (difference)
Exercises
Module J: File Handling
J.1 Introduction
J.2 Writing/Reading/appending data to a file
J.3 Additional file methods
J.4 Dictionary (about pickle)
Exercises
Module K: OOPS
K.1 Introduction
K.2 Creating classes, methods, and instance
K.3 Constructor or Destructor method
K.4 Inheritance
K.5 Polymorphism
K.6 Data Abstraction
K.7 Special methods
Exercises
Level Advanced • 17 Lectures • 00 Minutes
1 lectures, 00:00:00 min
Day1_ Basic to Machine Learning- Introduction of Machine Learning
1 lectures, 00:00:00 min
Day2_ Basic Machine Learning Training - Introduction to Regression
1 lectures, 00:00:00 min
Day3_ Basic Machine Learning Training - Classification, KNN, Decision Trees
1 lectures, 00:00:00 min
Day4_ Basic Machine LearningTraining- Clustering, K-Mean, Hierarchical Clustering
1 lectures, 00:00:00 min
Day5_ Basic Machine Learning Training - Linear Algebra
1 lectures, 00:00:00 min
Day6_ Basic Machine Learning Training -Linear Algebra and Introduction to Calculus
1 lectures, 00:00:00 min
Day7_ Basic Machine Learning Training - Diffrentiation
1 lectures, 00:00:00 min
Day8_ Basic Machine Learning Training - MINI PROJECT _Sentiment Analysis_pt. 1
1 lectures, 00:00:00 min
Day9 _ Basic Machine Learning Training - MINI PROJECT _Sentiment Analysis_ pt. 2
1 lectures, 00:00:00 min
Day10_ Basic Machine Learning Training - Partial Diffrentiation
1 lectures, 00:00:00 min
Day11_ Basic Machine Learning Training - Probability and Statistic
1 lectures, 00:00:00 min
Day12_ Basic Machine Learning - Conditional Probability
1 lectures, 00:00:00 min
Day13_ Basic Machine Learning- MINI PROJECT _Customer Spending Analysis_
1 lectures, 00:00:00 min
Day14_ Basic Machine Learning Training - MINI PROJECT - Customer Spending Analysis
1 lectures, 00:00:00 min
Day15_ Basic Machine Learning Training- MINI PROJECT - Customer Segmentation Analysis pt3
1 lectures, 00:00:00 min
Day16_ Basic Machine Learning Training - Statistics pt 1
1 lectures, 00:00:00 min
Day18_ Basic Machine Learning Training - Introduction of Neural Network
00 Minutes On Demand Video
Full lifetime access
Access on mobile and TV