Machine Learning Training

Mindmajix Technologies

Acquaint yourself with the core concepts of machine learning through the online training by Mindmajix.

Online

₹ 11200 14000

Important Dates

04 Feb, 2025

Course Commencement Date

08 Feb, 2025

Course Commencement Date

11 Feb, 2025

Course Commencement Date

particular

details

                                    Medium of instructions
                                    English

                                    Mode of learning
                                    Self study, Virtual Classroom

                                    Mode of Delivery
                                    Video and Text Based

                                    Frequency of Classes
                                    Weekdays, Weekends

Python Programming

Introduction to Python

Anaconda Navigator Download & Installation

Anaconda Navigator Download
Anaconda Navigator Installation
Create environment and download libraries
Introduction to jupyter notebook
Python Object & Data Structure
Python Statement
Methods and Function
OOPs
Python Libraries

Python Object & Data Structure

Numbers
String
List
Dictionary
Tuples
Sets and Booleans

Python Statement

Intro python state , if elif else
For loop
While loops , Useful Operators

Methods and Function

lambda expression , nested statement

OOPs

OOPs basics
OOPs inheritance
OOPs polymorphism

Python Libraries

Numpy
Pandas
Matplotlib
seaborn

Python Object & Data Structure

Numbers

Basic Arithmetic
Variable assignment

String

String
String indexing and slicing
String properties

List

Lists
List method
List comprehensions

Dictionary

Construct Dict
Dict Methods

Python Statement

Intro python state , if elif else

introduction to python statements
if, elif and else statement part 1
if, elif and else statement part 2

For loop

Introduction to for loops
For loop examples

While loops , Useful Operators

while loop
break , cont , pass
useful operator part 1
useful operator part 2

Methods and Function

lambda expression , nested statement

map and filter
lambda expression
nested statement part 1
nested statement part 2
methods
functions part 1
functions part 2
list compressions

Python Libraries

Numpy

Creating array
Using array and scalers
Indexing arrays
Array transposition
Universal array functions
Array processing

Pandas

Series
Index objects
Reindex
Drop entry
Selecting entries
Data alignment
Rank and sort
Missing Data

Seaborn

Seaborn categorical plots part 1
Seaborn categorical plots part 2
Seaborn categorical plots part 3
Seaborn distribution plot part 1
Seaborn distribution plot part 2
Seaborn regression plot
Seaborn style and color

What is Machine Learning

Machine Learning application
Machine learning Process
How to become a machine learning engineer
Pattern Recognition

Artificial intelligence

What is AI
What is deep learning
AI tools and Models

Graphica Models

What is PGM
MRF

Stats and Prob

Introduction to statistic
Statistical analysis process
Kurtosis
Co-relation matrix
Statistics practical

Data Pre-Processing

Data preparation process
Type of Data
Feature Scaling

Machine Learning Types

Logistic reg
Multi and poly regression
Simple linear regression

Logistic reg

Logistic regression Data preprocessing
Feature scaling _ model making
Visualize training results

Multi and poly regression

Multiple linear regression
Polynomial regression part 1
Polynomial regression part 2

Simple linear regression

Regression data preprocessing
Regression model making
Supervised learning introduction
Linear regression
LMS algorithm
Objective and application of linear regression
Multiple and polynomial regression
Logistic regression
Objective and model eval
Intro unsupervised learning
Semi-supervised and important consideration

KNN

KNN practical

KNN practical

KNN Data preprocessing
KNN modeling
Visualize KNN model

Decision Tree

dt classifier
dt regressor
RF practical
Decision tree regression
Decision Tree Classification
Random Forest

dt classifier

Decision tree Classifier
Visualize the DT

dt regressor

step 1 making DT regression
step 2 DT Structure

RF practical

RF practical part 1
RF practical part 2

SVM

SVM introduction
SVM Mathematics
Non-linear SVM

Clustering Analysis

Clustering Introduction
K-means theory
k-means Mathematical
kmeans practical part 1
kmeans practical part 2

ANN

Rise of artificial neuron
Introduction to ANN
Perceptron
Activation Functions
Feed forward Neural networks
Cost function in neural network
Back-propagation neural network
Introduction to CNN
CNN arch and Convolutional layer
Pooling layer and fully connected layer
RNN introduction
Recurrent neurons
Various configuration of RNNs
Training recurrent neural network
Tensorflow Introduction
Computationsl Graph
ANN practical
CNN Practical
RNN Practical

ANN Practical

Intro to ANN
Part 1 data preprocessing
Part 2 building ANN
Part 3 testing ANN

CNN Practical

Import libraries
Part 1 data preprocessing
Part 2 Building the CNN
Part 3 Training CNN
Part 4 making a single prediction

RNN Practical

Part 1 data preprocessing
Part 2 Building RNN
Part 3 testing the model

NLP

Basics of NLP
NLP application
Feature extraction
Gaussian NB
NLP practicals

NLP practicals

NLP practical part 1
NLP practical part 2
NLP practical part 3

Reinforcement Learning

Rf intro
Case study overview
Bellman eq
MDP
Q-learning
Dynamic programming
Q-learning practical

Q-learning practical

Q-learning practical part 1
Q-learning practical part 2
Q-learning practical part 3

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Machine Learning Training

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₹ 11200 14000

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What you will learn

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Python Programming

Anaconda Navigator Download & Installation

Python Object & Data Structure

Python Statement

Methods and Function

OOPs

Python Libraries

Python Object & Data Structure

Numbers

String

List

Dictionary

Python Statement

Intro python state , if elif else

For loop

While loops , Useful Operators

Methods and Function

lambda expression , nested statement

Python Libraries

Numpy

Pandas

Seaborn

What is Machine Learning

Artificial intelligence

Graphica Models

Stats and Prob

Data Pre-Processing

Machine Learning Types

Logistic reg

Multi and poly regression

Simple linear regression

KNN

KNN practical

Decision Tree

dt classifier

dt regressor

RF practical

SVM

Clustering Analysis

ANN

ANN Practical

CNN Practical

RNN Practical

NLP

NLP practicals

Reinforcement Learning

Q-learning practical

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