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Machine Learning Certification Training

$400.00 $250.00

Description

What is Machine Learning?

Machine Learning is the field of study that empowers machines to learn without explicit programming. ML is one of the most innovative developments one’s ever seen.

ML Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using Python and R. Data Science Training encompasses a conceptual understanding of Statistics, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR.

Course Outcome: –

On completion of this course, the students will be able to

Understand the basic concepts of ML.

Understand how to use different python libraries in ML.

Work with different Regression and Classification Algorithms.

Perform syntax and semantics in ML with Python.

Ability to design and analyse various ML algorithms.

Apply different concepts of ML in other application areas.

Session 1 Introduction:

What is Machine Learning?

Applications of Machine Learning

ML Types of Learning- Supervised vs Unsupervised Learning

Python libraries suitable for Machine Learning

Session 2 Data Pre-processing:

Missing Value

Categorical Data

Splitting Dataset

Feature Scaling

Session 3 Regression:

Introduction to Regression

Types of Regression

Simple Linear Regression

Multiple Linear Regression

Polynomial Regression

Decision Tree Regression

Random Forest Regression

Session 4 Classification:

Basic Concept of Classification

Classification vs Regression

Logistic Regression

K-NN

SVM

Kernel SVM

Naive Bayes

Decision Tree Classification

Random Forest Classification

Session 5 Clustering:

K-Means

Hierarchical Clustering

Session 6 Natural Language Processing:

NLTK installation

Tokenization

Case Study: Document Classification

Session 7 Deep Learning:

Artificial Neural Networks

Convolutional Neural Networks

Session 8 Dimensionality Reduction:

Introduction to Dimensionality Reduction

Principal Component Analysis (PCA)

LDA

Kernel PCA

Prerequisites: –

1.Basic of any programming knowledge but Python is preferred.

2.The student should have good logical and reasoning skill.

Duration & Timings :

Duration – 30 Hours.

Training Type: Online Live Interactive Session.

Faculty: Experienced.

Weekend Session – Sat & Sun 9:30 AM to 12:30 PM (EST) – 5 Weeks. December 5, 2020.

Weekday Session – Mon – Thu 9:30 PM to 11:30 PM (EST) – 4 Weeks. December 28, 2020.

 Inquiry Now         Discount Offer 

USA: +1 734 418 2465 | India: +91 40 4018 1306

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