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Machine Learning Course

Machine-Learning

Machine Learning Course Description

 

What’s behind the machine learning hype? In this non-technical course, you’ll learn everything you’ve been too afraid to ask about machine learning. There’s no coding required. Hands-on exercises will help you get past the jargon and learn how this exciting technology powers everything from self-driving cars to your personal Amazon shopping suggestions. How does machine learning work, when can you use it, and what is the difference between AI and machine learning? They’re all covered. Gain skills in this hugely in-demand and influential field, and discover why machine learning is for everyone!

 

 

What is Machine Learning?

In this chapter, we’ll define machine learning and its relation to data science and artificial intelligence. Then, we’ll unpack important machine learning jargon and end with the machine learning workflow for building models.

 

  • What is machine learning?
  • Recognizing handwritten digits
  • AI, data science, and machine learning walk into a bar…
  • What’s true about machine learning?
  • Machine learning concepts
  • Machine learning lingo
  • Supervised vs unsupervised
  • Machine learning workflow
  • Steps for building a model
  • A true step

 

Machine Learning Models

Now that you know the basics of machine learning, let’s dive a little bit deeper. At the end of this chapter, you will know the different types of machine learning, as well as how to evaluate and improve your models.

  • Supervised learning
  • Warm up
  • Regressing with class
  • Unsupervised learning
  • We don’t need any supervision
  • Gotta cluster ’em all!
  • Evaluating performance
  • True or False?
  • Land of confusion
  • Improving performance
  • It’s a long way to the top
  • Explore hyperparameter tuning

Deep Learning

In this chapter, we’ll unpack deep learning beginning with neural networks. Next, we’ll take a closer look at two common use-cases for deep learning: computer vision and natural language processing. We’ll wrap up the course discussing the limits and dangers of machine learning.

    • Deep learning
    • What is deep learning?
    • Should I use deep learning?
    • Computer vision
    • Image data
    • The process
    • Recognizing handwritten digits
    • Natural Language Processing
    • Sentiment analysis
    • Classifying machine learning tasks
    • Bag of words
    • Limits of machine learning
    • To black box or not to black box?
    • Spotting bias in machine learning
    • Congratulations!

 

 

Machine Learning Course Features

  • Training Duration – 2 Months
  • Total – 16 Classes
  • Weekly – 2/3 Classes
  • Course Fee –  10,000/- + VAT
  • Payment Option – If you want to know the payment options of MahbubOsmane.com visit here.

MahbubOsmane.com’s Address

 

  • MahbubOsmane.com – Digital Marketing Blog
  • Address: Ka/65/5, Shahjadpur, Gulshan, Dhaka-1212
  • Phone: +88 01716 988 953 or +88 01912 966 448
  • Email: hi@mahbubosmane.com
  • Skype: mrpsoft.2
  • Web: www.mahbubosmane.com

Relevant SEO Services By MahbubOsmane.com

 

Still, have questions? Or want to get a call?

 

Just fill-up the contact form or call us at +88 01716 988 953 or +88 01912 966 448 to get a free consultancy from our expert or you can directly email us at hi@mahbubosmane.com We would be happy to answer you.

    MahbubOsmane.com’s Exclusive Services

    Conclusion

     

    Above all, I will tell you, with the increase of digital business, the Machine Learning Course is very important. So, there has a great opportunity to build an amazing career. On the other hand, MahbubOsmane.com, the best Machine Learning Course in Bangladesh is helping you to start your machine learning journey. Similarly, you have the opportunity to work from home as a freelancer and as a full-time employee at the corporate level.

    Will you stay backward with this digital world? A digital and creative career can give you a huge opportunity to build a golden future. Welcome to MahbubOsmane.com’s Machine Learning Course in Bangladesh. Welcome in advance again and have a good journey in the Machine Learning world.

     

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