Deep Learning Explained

MOOC
Deep Learning Explained
Language
English
Duration
2 months
Certificate
Certification paid
Course by EdX
Deep Learning Explained
What will you learn?
The components of a deep neural network and how they work together
The basic types of deep neural networks (MLP, CNN, RNN, LSTM) and the type of data each is designed for
A working knowledge of vocabulary, concepts, and algorithms used in deep learning
How to build: An end-to-end model for recognizing hand-written digit images, using a multi-class Logistic Regression and MLP (Multi-Layered Perceptron)
A CNN (Convolution Neural Network) model for improved digit recognition
An RNN (Recurrent Neural Network) model to forecast time-series data
An LSTM (Long Short Term Memory) model to process sequential text data
About the course

Machine learning uses computers to run predictive models that learn from existing data to forecast future behaviors, outcomes, and trends. Deep learning is a sub-field of machine learning, where models inspired by how our brain works are expressed mathematically, and the parameters defining the mathematical models, which can be in the order of few thousands to 100+ million, are learned automatically from the data.

Deep learning is a key enabler of AI powered technologies being developed across the globe. 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 approaches will be translated into working code with practical problems and hands-on experience. You will learn how to build and derive insights from these models using Python Jupyter notebooks running on your local Windows or Linux machine, or on 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.

edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.

Note : These courses will retire in June. Please enroll only if you are able to finish your coursework in time.

Program
Deep Learning Explained
Learn an intuitive approach to building the complex models that help machines solve real-world problems with human-like intelligence.
Lecturers
Steve Elston
Steve Elston
Managing Director Quantia Analytics, LLC
Platform
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All the courses on this platform are free of charge. The authors are top universities and corporations that seek to maintain high quality standards. If you do not meet a deadline for assignments, you lose points. Like on other platforms, the videos in which the theory is explained are followed by practical assignments. Courses are available in English, Chinese, Spanish, French and Hindi.
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