Artificial Neural Networks

Introductions to AI/ML and DL. In this week you will learn "Artificial Neural Networks, Backpropagation in ANNs, Activation Functions, Loss Functions, Optimizers, XOR Problem in NumPy and Many More"

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Artificial Neural Networks

Introductions to AI/ML and DL. In this week you will learn "Artificial Neural Networks, Backpropagation in ANNs, Activation Functions, Loss Functions, Optimizers, XOR Problem in NumPy and Many More"

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Includes:
  • Verifiable certificate
  • Quiz & mock tests
  • Live mentor workshops
  • 2 devices access*
Course Description

In this week you will be learning “HTML Basics, Basic Tags, HTML Attributes, Form Validations and Many More”. We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed in the industry. This course has a tremendous amount of content and resources so that you can learn everything you need to know - whatever is appropriate for your ability level. You will be able to learn at your own pace. You will always be able to come back to the content to review it or learn additional concepts when you are ready for them. You will get great value from this course and, more importantly, you will have a great time learning.

 

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What you will learn?
  • Artificial Neural Networks
  • Implementation of Artificial Neural Networks
  • Backpropagation in ANN's
  • Activation Functions
  • Loss Functions
  • Batches and Mini-Batches
  • Optimizers
  • Regularization Techniques
  • Initialization of weights and biases
  • Machine Learning Frameworks
  • Introduction to Google Colaboratory
  • XOR Problem in NumPy
  • Titanic Classification in Numpy
  • Titanic Classification in TensorFlow
  • Titanic Classification in PyTorch
  • Titanic Classification in Keras
Requirements
  • No Prerequisites Required
Course Curriculum
Introduction to Artificial Intelligence
17 Lessons
  • Artificial Neural Networks
  • Implementation of Artificial Neural Networks
  • Backpropagation in ANNs
  • Activation Functions
  • Loss Functions
  • Batches and Mini-Batches
  • Optimizers
  • Regularization Techniques
  • Initialization of Weights and Biases
  • Machine Learning Frameworks
  • Introduction to Google Colaboratory
  • XOR Problem in NumPy
  • Titanic Classification in Numpy
  • Titanic Classification in TensorFlow
  • Titanic Classification in PyTorch
  • Titanic Classification in Keras
  • Quiz

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