Approved by Habanero Data
Deep Learning
next available COURSE:
Duration :
4 Day/s
DURATION
4 Day/s
USD $
550
USD
$ 550
NGN ₦
250,000
NGN
₦ 250,000

Course Information

Everything you need to know

  • Course Syllabus
  • Your trainer
  • Key Information

About the Course:
This four-day course is designed for beginners who want to have a basic understanding of AI and Deep Learning. Identify different solutions it offers to problems and its fundamental concepts. Industries like healthcare, information technology, fin-tech, and e-commerce industries can benefit from professionals in this field.

Day 1
 
Introduction to Deep Learning

  • Neural Networks Basics
  • Binary Classification
  • Logistic Regression
  • Gradient Descent
  • Derivatives
  • Computation Graph
  • Logistic Regression Gradient Descent
  • Gradient Descent on m Examples
  • Vectorization
  • Broadcasting in Python
  • Shallow neural networks
  • Neural Networks Overview
  • Neural Network Representation
  • Computing a Neural Network’s Output
  • Vectorized Implementation
  • Activation functions
  • Gradient descent for Neural Networks

 
Deep Neural Networks

  • Forward Propagation in a Deep Network
  • Building blocks of deep neural networks
  • Forward and Backward Propagation
  • Parameters vs Hyperparameters
  • Train / Dev / Test sets
  • Bias / Variance
  • Regularization
  • Understanding Dropout
  • Normalizing inputs
  • Weight Initialization for Deep Networks
  • Numerical approximation of gradients
  • Mini-batch gradient descent
  • Exponentially weighted averages
  • Gradient descent with momentum
  • RMSprop
  • Learning rate decay
  • The problem of local optima
  • Hyperparameters
  • Tuning process
  • Batch Normalization
  • Normalizing activations in a network
  • Fitting Batch Norm into a neural network
  • Programming Frameworks
  • Deep learning frameworks
  • TensorFlow

 

Machine Learning Strategy I

  • Machine Learning Strategy
  • Why ML Strategy
  • Orthogonalization
  • Single number evaluation metric
  • Satisficing and Optimizing metric
  • Train/dev/test distributions
  • Size of the dev and test sets
  • Avoidable bias
  • Understanding human-level performance
  • Surpassing human-level performance
  • Improving your model performance

 
Machine Learning Strategy II

  • Carrying out error analysis
  • Cleaning up incorrectly labeled data
  • Build your first system quickly, then iterate
  • Training and testing on different distributions
  • Bias and Variance with mismatched data distributions
  • Addressing data mismatch
  • Transfer learning
  • Multi-task learning
  • End-to-end deep learning

 

Conclusion

  • Summary

Our international certified trainers have highly experienced Deep Learning practitioners who have real-world expertise.

I – Laptops will be provided for all candidates with pre-installed Microsoft Cognotive Toolkit.

II – Our training venue is based in Lekki, Lagos (Specific venue will be emailed on confirmation of a place on the course).

III – Lunches and refreshments are provided inclusive of the cost. Wi-fi and access to spaces to take private calls are also available.

For more information on our training, please enquire using the form above or call +2348103382376

Deep Learning

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    ONLINE TRAINING
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    Course Schedule

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    Deep Learning

    Available Dates

    Available Places

    Book or Enquire

    August 23, 2021

    Abuja, Accra, Addis Ababa, Freetown, Kigali, Lagos, Nairobi

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    Call our team today on +2348103382376 or email training@habanerodata.net

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