Key Features
  • Lifetime Access

  • CloudLabs

  • 24x7 Support

  • Real-time code analysis and feedback

  • 100% Money Back Guarantee

PDP BG 1
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What is Machine Learning Course about?

earn machine learning principles with in-depth practical exposure to how projects are implemented at organizations in this machine learning course. You learn all about real-world applications of ML using Python & the essentials of statistics and ML models with expert guidance from experienced industry mentors.

Our ML training includes Cloudlabs integration so you gain hands-on experience working with Python libraries. Create supervised learning models using regression, random forest classification, SVM and Naïve Bayes classifiers. Develop unsupervised learning models using k-means clustering and association rule learning. Equip yourself with the skills needed to build ML models from Day 1.

What are the objectives of Machine Learning Course ?

At the end of this Machine Learning course, you will be able to:

  • Quickly start developing ML models while learning underlying theory
  • Understand the key components of any ML model
  • Learn machine learning algorithm types and develop an appreciation for their real-world applications
  • Develop programs in Python using built-in libraries
  • Recognize the statistical principles that forms the foundation of ML
  • Develop Supervised learning models
  • Develop Unsupervised learning models
  • Use various methods for testing machine learning training models
  • Work on application development projects at your organization that employ machine learning 
Available Training Modes

Live Online Training

12 Hours

Classroom Training

 

2 Days
PDP BG 2

Who is Machine Learning Course for?

  • Anyone looking to incorporate ML algorithms into their applications
  • Teams getting started on machine learning projects 

What are the prerequisites for Machine Learning Course?

Course Outline

  • Applications of Machine Learning
    • Web Search Ranking
    • Ecommerce
    • Weather forecast
    • Malware stop/Anti-virus
    • Anti-spam
    • Natural Language Processing in search engine
    • Face detection
    • Speech Recognition
  • Jumpstart Python Programming
    • Install Anaconda Bundle
    • Starting Jypyter Notebook
    • Data Types in Python - Integer, Float, String
    • Data Structures in Python
    • Control Flow in Python
    • Functions in Python
    • Importing libraries
    • Quickstart NumPy
    • Quickstart Pandas
    • Quickstart Matplotlib
    • Quickstart Scikit-Learn
    • Quickstart Seaborn
  • Quick Stats for Machine Learning
    • Descriptive Statistics
    • Distributions
    • Hypothesis Testing
    • Maximum Likelihood
  • Supervised Learning
    • Usecases of Supervised Learning
    • Classification
    • Linear Regression
    • Random Forest Classification
    • Support Vector Machines (SVM) Classification
    • Naive Bayes
  • Unsupervised Learning
    • Usecases of Unsupervised Learning
    • k-Means Clustering
    • Apriori - Association Rule Learning
  • Reinforcement Learning
    • Use cases of Reinforcement Learning
  • Key Elements of Machine Learning
    • Representation
    • Evaluation
    • Optimization
  • Types of Learning
    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning

Who is the instructor for this training?

The trainer for this ML course has extensive experience in data analysis, programming, and machine learning, including years of experience mentoring professionals on machine learning certification courses.

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