Deep Learning Zero-Hero

Become a " Deep Learning" Specialist. In this learning path, you will learn " Python, Dimensionality Reduction & Deep Learning"

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Verifiable Certificate

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Deep Learning Zero-Hero

Become a " Deep Learning" Specialist. In this learning path, you will learn " Python, Dimensionality Reduction & Deep Learning"

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

Become a Deep Learning Specialist.

Deep learning is at the cutting-edge of intelligent automation. From speech-to-text, and object detection, to image recognition and driverless cars and moreover mastering video games like Dota or beating the world champion in AlphaGo, deep learning is used everywhere. As the increasing demand of in market for the people for jobs in field of Deep Learning, it has become one of the most desired skills for well paid jobs on the planet as it is bringing out some very key advancement in technological space. Troubled on how to begin? Don’t worry as we, bring to you an amazing career path course on “Deep Learning” which will take you to an amazing journey and help you in learn Deep Learning with best-in-class content covering all topics starting from Python, Dimensionality Reduction, Deep Learning and much more.  Come join us and be the part of 21st century’s data revolution.

What you will learn?
  • Python Basics
  • Python Data Structures
  • Python Functions
  • Linear Principal Component Analysis
  • Kernel Principal Component Analysis
  • Thresholding Numerical Feature Variance
  • Handling Highly Correlated Features
  • Automatic Feature Selection
  • Introduction To neural Network
  • Improving Deep Neural Networks
  • Optimization Algorithms
  • Foundation Of CNN
  • Deep Convolutional Model
  • Special Application
  • RNN
Requirements
  • No Prerequisites Required
Course Curriculum
  • Module - 1: Python Zero-1
    Go Zero-One by learning the much-needed fundamentals of “Python". In this course, you will learn " Python Basics, Python Data Structure, Python Functions"
    Section 1: Python Basics
    6 Lessons
    • Introduction and Setup
    • Variables and Expressions
    • Input and Output
    • Conditional Statements
    • Iterations and Loops
    • Strings and String Formatting
    • Lists, Indexing and Slicing
    • Tuple
    • Dictionaries
    • Functions
    • Lambda functions and mapping
    • args and kwargs
  • Module - 2: Dimensionality Reduction Techniques
    Go Zero-One by learning the much-needed fundamentals of “Dimensionality Reduction Techniques". In this course, you will learn " Linear Principal Component Analysis, Kernel Principal Component Analysis, Automatic Feature Selection".
    Section 1: Dimensionality Reduction
    5 Lessons
    • Linear Principal Component Analysis
    • Kernel Principal Component Analysis
    • Thresholding Numerical Feature Variance
    • Handling Highly Correlated Features
    • Automatic Feature Selection
  • Module - 3: Deep Learning
    Go Zero-One by learning the much-needed fundamentals of “Deep Learning". In this course, you will learn " Neural Network, Deep Neural Networks, Optimization Algorithms, Foundation of CNN".
    Section 1: Introduction to Neural Network
    12 Lessons
    • Neural Network Representation
    • Computing a Neural Network's Output
    • Activation functions
    • Derivatives of activation functions
    • What is Neural Networks.
    • Revisiting Binary Classification And Logistic Regression
    • Gradient Descent
    • Computation Graph and It's Derivative
    • Gradient descent for Logistic Regression
    • Gradient Descent Over m Training Examples
    • Vectorization
    • Vectorization Of Logistic Regression
    • Deep L-layer neural network
    • Forward Propagation in Deep Networks
    • Dropout Regularization
    • Normalizing Input
    • Vanishing_Exploding Gradients
    • RMS Convolution
    • Learning Rate Decay
    • Why Convolution
    • Edge Detection Example
    • Padding
    • Strided Convolutions
    • Convolution Over Volume
    • One Layer Of Convolutional Network
    • Simple Convolutional Network Example
    • Pooling Layers
    • Classic Networks
    • ResNet
    • Transfer Learning
    • Data Augmentation
    • Neural Style Transfer
    • Introduction to RNN's
    • Different Types of RNN's
    • Brief Introduction of GRU and LSTM
  • Certificate
    Once you've successfully completed the course, You will receive the certificate

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