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60% Complete Courses » Machine Learning
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Introduction to Machine learning
What is AI
What is machine learning
History of machine learning
Uses of machine learning

Types of machine learning
Supervised learning
Unsupervised learning
Reinforcement learning
Transfer learning

Data Science and machine learning
Definition of Data Science
Why data science
Roles for machine learning projects

Managaing Data Analysis
Defining the process
Building the data team
Experimental data design
Data storage and privacy

Tools for machine learning
Programming languages
Data repositories
Hierarchical databases
Software used

Basics of R programming
Installing R Studio
Matrix operations
Data loading/unloading
Plotting and visualizing
Algorithms - Predicting and modelling

Statistical methods
Graph theory
Probability
Bayes theorem
Regression models

Data modelling - Linear regression
Model representtion
Cost function
Gradient descent for linear regression

Data modelling - Logistic regression
Hypothesis representation
Decision boundary

Decision trees
Basics of decision trees
Uses for decision trees
Advantages and limitations
How decision trees work

Decision trees example
create a decision tree
Requirement
Training the data

Classifiers
Types of classifiers
Bernoulli classifier
Ridge classifier
Support vector machines

Support vector machines
Linear and non linear classification
What are SVM
Where are SVM used

Association rules learning
What is ARL
Where are ASL rules used
Support, Confidence, lift and conviction

NLP
History of NLP
Statistical NLP
NLP tasks

NLP example
Apache Open NLP
Natural language toolkit
Stanford NLP
Example of anlp use cases

Clustering
What is clustering
Where is clustering used
Clustering mode

Clustering K means Model example
Preparing the data
Workbench method
Commandline method
Coded method

Big Data with machine learning
Machine Learning and battch process
Examples of Big data Process Framework
Hadoop Framework
Mahout Framework

Deep learning
Why Deep Learning
what is deep learning
Examples of Deep Learning

Basics of neural networks
Introduction to Neural Networks
Why Study Neural Networks
Real life examples of neural network

Types of neural networks
perceptron
Recurrent neural networks
convolutional neural network

Real life example of neural network
image recognition
Text analytics

Anomaly Detection
Anomaly detection systems
Choosing what feature to use

Chatbot and its applications
how chatbot works
Examples of real life chatbots

Course Id:
ML001 
Course Fees:
401 USD