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[FreeCoursesOnline.Me] [Packtpub.Com] Python Deep Learning for Beginners - [FCO]

[FreeCoursesOnline.Me] [Packtpub.Com] Python Deep Learning for Beginners - [FCO]

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Description




By: Rudy Lai

Released: Friday, November 30, 2018 New Release!

Torrent Contains: 33 Files, 10 Folders

Course Source: https://www.packtpub.com/big-data-and-business-intelligence/python-deep-learning-beginners-video



Apply deep learning concepts and use Python to solve challenging tasks



Video Details



ISBN 9781788629942

Course Length 2 hours 39 minutes



Table of Contents



• UNDERSTANDING DEEP LEARNING

• BUILDING THE BASIC BLOCKS OF MACHINE LEARNING

• DIVING INTO DEEP NEURAL NETWORKS

• DISCOVERING CONVOLUTIONAL NEURAL NETWORKS (CNNS)

• USING CNNS TO SOLVE INCREASINGLY COMPLEX TASKS

• LEARNING ABOUT DETECTION AND SEGMENTATION

• EXPLORING RECURRENT NEURAL NETWORKS

• OBJECT DETECTION USING CNNS

• MOVING FORWARD WITH DEEP LEARNING AND AI



Video Description



We avoid complex math equations, which can often be a barrier to entry for newcomers.

This course will teach you to apply deep learning concepts using Python to solve challenging tasks. You'll build a Python deep learning-based image recognition system and deploy and integrate images into web apps or phone apps.

You will start out with an intuitive understanding of neural networks in general. We will guide you through the building blocks of deep learning networks to tackle complex neural networks.

So, take this course and learn the skills and temperament need to enter the AI marketplace today.



Style and Approach



A direct, practical, and very hands-on approach where we deal less with theory and adopt a more hands-on style of learning.



What You Will Learn



• The history of neural networks, and where they are now

• Get a brief understanding of trade-offs and practical implementation aspects

• Get hands-on experience building basic neural network models (no math!) using Python

• Ramp up productivity in model building by leveraging popular frameworks

• Implement some state-of-the-art computer vision algorithms using deep learning and Python

• Build and learn to deploy a practical deep learning application with Python

• Get an overview of current skills, frameworks, tools, and techniques for the AI market

• Build a deep learning-based image recognition system using Python and learn how to deploy and integrate it into web apps or phone apps



Authors



Rudy Lai



Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, Machine Learning, and cloud computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the world's most popular soft drink s companies, helping each of them to make better sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action. read more at source.



For More Udemy Free Courses >>> http://www.freetutorials.eu

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Our Forum for discussion >>> https://discuss.freetutorials.eu/








File list
  • [FreeCoursesOnline.Me] [Packtpub.Com] Python Deep Learning for Beginners - [FCO]
  • 1.Understanding Deep Learning/01.The Course Overview.mp4 6.1 MB
  • 1.Understanding Deep Learning/02.A Brief History of Deep Learning.mp4 5.1 MB
  • 1.Understanding Deep Learning/03.Deep Learning Today.mp4 11.6 MB
  • 1.Understanding Deep Learning/04.Tools, Requirements, and Setup.mp4 20 MB
  • 2.Building the Basic Blocks of Machine Learning/05.Exploring Supervised Learning.mp4 3.8 MB
  • 2.Building the Basic Blocks of Machine Learning/06.Representational Learning and Feature Engineering.mp4 8.4 MB
  • 2.Building the Basic Blocks of Machine Learning/07.Linear Regression.mp4 18.9 MB
  • 2.Building the Basic Blocks of Machine Learning/08.The Perceptron.mp4 14 MB
  • 3.Diving into Deep Neural Networks/09.Feedforward Networks.mp4 8.5 MB
  • 3.Diving into Deep Neural Networks/10.Backpropagation.mp4 10.4 MB
  • 3.Diving into Deep Neural Networks/11.Neural Networks from Scratch.mp4 9 MB
  • 3.Diving into Deep Neural Networks/12.Overfitting and Regularization.mp4 7.5 MB
  • 4.Discovering Convolutional Neural Networks (CNNs)/13.Understanding CNNs.mp4 13.5 MB
  • 4.Discovering Convolutional Neural Networks (CNNs)/14.Implementing a CNN.mp4 15.6 MB
  • 4.Discovering Convolutional Neural Networks (CNNs)/15.Deep CNNs.mp4 14.2 MB
  • 5.Using CNNs to Solve Increasingly Complex Tasks/16.Very Deep CNNs.mp4 10.2 MB
  • 5.Using CNNs to Solve Increasingly Complex Tasks/17.Batch Normalization.mp4 7.5 MB
  • 5.Using CNNs to Solve Increasingly Complex Tasks/18.Fine-Tuning.mp4 12 MB
  • 6.Learning about Detection and Segmentation/19.Semantic Segmentation.mp4 9.3 MB
  • 6.Learning about Detection and Segmentation/20.Fully Convolutional Networks.mp4 12.6 MB
  • 7.Exploring Recurrent Neural Networks/21.Recurrent Neural Networks.mp4 17 MB
  • 7.Exploring Recurrent Neural Networks/22.LSTM and Advancements.mp4 12.4 MB
  • 8.Object Detection Using CNNs/23.Building a CNN to Detect General Images.mp4 19 MB
  • 8.Object Detection Using CNNs/24.Training and Deploying on a Cluster.mp4 14.5 MB
  • 9.Moving Forward with Deep Learning and AI/25.Comparison of DL Frameworks.mp4 15.2 MB
  • 9.Moving Forward with Deep Learning and AI/26.Exciting Areas for Upcoming Research.mp4 9.8 MB
  • Discuss.FreeTutorials.Us.html 165.7 KB
  • Exercise Files/code_35662.zip 12.6 KB
  • FreeCoursesOnline.Me.html 108.3 KB
  • FreeTutorials.Eu.html 102.2 KB
  • Presented By SaM.txt 33 B

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