Deep Learning Explained Training

Live Online & Classroom Enterprise Training

Deep learning is a key enabler of AI-powered technologies being developed globally.

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What is Deep Learning Explained Course about?

In this deep learning course, you will learn an intuitive approach to building complex models that help machines solve real-world problems with human-like intelligence. The intuitive methods will be translated into working code with practical problems and hands-on experience. You will learn to build and derive insights from these models using Python Jupyter notebooks on your local Windows or Linux machine or a virtual machine running on Azure. Alternatively, you can leverage the Microsoft Azure Notebooks platform for free.

This course provides the level of detail needed to enable engineers/data scientists/technology managers to develop an intuitive understanding of the key concepts behind this game-changing technology. At the same time, you will learn simple yet powerful "motifs" that can be used with lego-like flexibility to build an end-to-end deep learning model. You will learn how to use the Microsoft Cognitive Toolkit -- previously known as CNTK -- to harness the intelligence within massive datasets through deep learning with uncompromised scaling, speed, and accuracy.

What are the objectives of Deep Learning Explained Course ?

The theory and math underlying deep learning
How to build artificial neural networks
Architectures of feedforward and convolutional networks
The calculus and code of gradient descent
Fine-tuning deep network models

Who is Deep Learning Explained Course for?

Students in a deep learning course
Machine-learning enthusiasts
Anyone interested in mechanisms of AI (artificial intelligence)
Data scientists who want to expand their library of skills
Aspiring data scientists

What are the prerequisites for Deep Learning Explained Course?

None

Available Training Modes

Live Online Training

60 Hours

Self-Paced Training

60 Hours

Course Outline Expand All

Expand All

Module 1: Introduction to deep learning and a quick recap of machine learning concepts.

Module 2: Building a simple multi-class classification model using logistic regression

Module 3: Detecting digits in hand-written digit images, starting with a simple end-to-end model, to a deep neural network

Module 4: Improving the hand-written digit recognition with a convolutional network

Module 5: Building a model to forecast time data using a recurrent network

Module 6: Building text data application using recurrent LSTM (long short term memory) units

Who is the instructor for this training?

The trainer for this Deep Learning Explained Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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Heena Rajan

Mindtree

Deep Learning Explained Training

What is Deep Learning Explained Course about?

What are the objectives of Deep Learning Explained Course ?

Who is Deep Learning Explained Course for?

What are the prerequisites for Deep Learning Explained Course?

Available Training Modes

Course Outline Expand All

Expand All

Module 1: Introduction to deep learning and a quick recap of machine learning concepts.

Module 2: Building a simple multi-class classification model using logistic regression

Module 3: Detecting digits in hand-written digit images, starting with a simple end-to-end model, to a deep neural network

Module 4: Improving the hand-written digit recognition with a convolutional network

Module 5: Building a model to forecast time data using a recurrent network

Module 6: Building text data application using recurrent LSTM (long short term memory) units