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Introduction to TensorFlow in Python

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5

(3)

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Computer vision algorithms that could distinguish between images from dogs and cats were not possible until a few decades ago. With a laptop, a skilled data scientist can classify thousands more objects with greater accuracy than the human eye using a computer. This course will show you how to use TensorFlow 2.0 to predict and train models that are used in important advances in image classification, recommendation systems and FinTech. You will learn both high-level APIs, which will allow you to design and train deep learning models in only 15 lines of code. Low-level APIs allow you to go beyond the basic routines. You will also learn how to accurately predict credit card defaults and housing prices.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Supervised Learning with scikit-learn

What You Will Learn

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Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow

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You will learn both high-level APIs, which will enable you to design and train deep learning models in 15 lines of code, and low-level APIs, which will allow you to move beyond off-the-shelf routines

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You will also learn to accurately predict housing prices, credit card borrower defaults, and images of sign language gestures

Course Instructors

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Isaiah Hull

Economist

Isaiah Hull is a senior economist in the research division at Sweden's Central Bank (Sveriges Riksbank) and the author of Machine Learning for Economics and Finance in TensorFlow 2. He holds a PhD in...

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