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MACHINE LEARNING TRAINING IN AHMEDABAD

Accelerate your career prospects with iteanz Machine Learning Training

About Program

Highest Quality and the Most Productive, High Energy Learning Experience.

Curriculum

Comprehensive Course Curriculum. Customizable to full-fill your trainer needs.

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About Program

Validate your skills as a MACHINE LEARNING expert

Achieving a MACHINE LEARNING certification exemplifies your expertise, and commitment and can advance your career. It’s an industry-recognized credential demonstrating your ability to design, deploy and operate applications and infrastructure on MACHINE LEARNING.

Machine learning certification is rated as the most valued IT Certification. Enroll Today!

We designed this cloud architect certification training for anyone seeking to learn the major components of Amazon Web Services (AWS). By the end of the course, you’ll be prepared to pass the associate-level AWS Certified Solutions Architect certification exam. The AWS certification is a must-have for any IT professional, and an AWS-certified solution architect takes home about $120,000 annually.

This course emphasizes AWS cloud best practices and recommended design patterns to help you think through the process of architecting optimal IT solutions on AWS. Case studies showcase how some AWS customers have designed their infrastructures and the strategies and services they implemented throughout the course.

Success Factors:

  • High-Quality Training
  • Top Technical Trainers
  • Comprehensive Course Curriculum
  • 100% Placement Assistance
  • Superb Satisfaction Score
  • Internship on Real-Time Project 
  • 3I- Individual Focus, Innovative & Interactive

Curriculum

CHAPTER 1:INSTALLATION AND CONFIGURATION

CHAPTER 2:DATA PREPROCESSING

CHAPTER 3:REGRESSION TECHNIQUES

  • Simple Linear Regression
  • Multiple Linear Regression
  • Polynomial Linear Regression
  • Support Vector Regression
  • Decision Tree Regression
  • Random Forest Regression
  • Evaluating Regression Model Performance

CHAPTER 4:CLASSIFICATION TECHNIQUES

  • K-Nearest Neighbors (KNN)
  • Support Vector Machine (SVM)
  • Kernel SVM
  • Naïve Bayes Classification
  • Decision Tree Classification
  • Random Forest Classification
  • Evaluating Classification Model Performance

CHAPTER 5:NATURAL LANGUAGE PROCESSING (NLP)

  • Basic of NLP
  • Language preprocessing Techniques
  • Auto summarizing the given text document

CHAPTER 6:CLUSTERING TECHNIQUES

  • K-Means Clustering
  • K-mini Batch Clustering
  • Hierarchical Clustering

CHAPTER 7:ELBOW METHOD

CHAPTER 8:CURVE SMOOTHENING TECHNIQUES

CHAPTER 9:ASSOCIATION RULE LEARNING

CHAPTER 10:REINFORCEMENT LEARNING

CHAPTER 11:BASICS OF NUMPY AND PANDA

CHAPTER 12:DEEP LEARNING

  • Basics/what is Deep Learning

CHAPTER 13:ARTIFICIAL NEURAL NETWORKS

  • Principal Component Analysis (PCA)
  • Linear Discriminant Analysis (LDA)

CHAPTER 14:STATISTICS BASICS

  • Standard Deviation
  • Variance
  • Co-Variance
  • T-distribution
  • Pearson Correlation Coefficient (PCC)/ Correlation Coefficient

CHAPTER 15:MODEL SELECTION

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It’s not just about training. It’s about career progress. Iteanz allows you to take control of your career by learning the right skills at the right time.

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