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Master Deep Learning using Case Studies : Beginner-Advance

 

Master Deep Learning using Case Studies : Beginner-Advance

GETT STARTED UDEMY COURSE COUPON
Master Deep Learning Algorithms Using Python From Beginner to Super Advance Level including Mathematical Insights. New

What you'll learn

  • Master Deep Learning on Python
  • Master Machine Learning on Python
  • Learn to use MatplotLib for Python Plotting
  • Learn to use Numpy and Pandas for Data Analysis
  • Learn to use Seaborn for Statistical Plots
  • Learn All the Mathmatics Required to understand Deep Learning Algorithms
  • Implement Deep Learning Algorithms along with Mathematic intutions
  • Real world projects of Deep Learning
  • Learning End to End Data Science Solutions
  • All Advanced Level Deep Learning Algorithms and Techniques like Regularisations , Dropout and many more included
  • Learn All Statistical concepts To Make You Ninza in Deep Learning
  • Real World Case Studies
  • Keras
  • Transfer Learning
  • Artifical Neural Network
  • Convolution Neural Network
  • Recurrent Neural Network
  • Feed Forward Network
  • Backpropogation

Requirements

  • Any Beginner Can Start this Course
  • 2+2 knowledge is more than sufficient as we have covered almost everything from scratch.
  • Prior Knowledge of Machine Learning is beneficial , if not we have covered all required pre-requisites in the course itself.

Description

Wants to become a good Data Scientist?  Then this is a right course for you.

  • This course has been designed by IIT professionals who have mastered in Mathematics and Data Science.  We will be covering complex theory, algorithms and coding libraries in a very simple way which can be easily grasped by any beginner as well.
  • We will walk you step-by-step into the World of Deep Learning. With every tutorial you will develop new skills and improve your understanding towards the challenging yet lucrative sub-field of Data Science from beginner to advance level.
  • We have solved few real world projects as well during this course and have provided complete solutions so that students can easily implement what have been taught.

We have covered following topics in detail in this course:

  • 1. Introduction
  • 2. Artificial Neural Network
  • 3. Feed forward Network
  • 4. Backpropogation
  • 5. Regularisation
  • 6. Convolution Neural Network
  • 7. Practical on CNN
  • 8. Real world project1
  • 9. Real world project2
  • 10 Transfer Learning
  • 11. Recurrent Neural Networks
  • 12. Advanced RNN
  • 13. Project(Help NLP)
  • 14. Generate Automatic Programming code
  • 15. Pre- req : Python, Machine Learning
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Online Course CoupoNED I am very happy that there are bloggers who can help my business

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