ลึกๆแล้ว มันอย่างนี้นี่เอง ... : Packt - Python Deep Learning for Beginners (Rudy Lai)




Python Deep Learning for Beginners [Video]
Rudy Lai

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.
All the code and this course's supporting files of are available on GitHub at
https://github.com/PacktPublishing/P...for-Beginners-

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

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

Authors
Rudy Lai
Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help their 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 drinks companies, helping each of them to better make sense of their data, and process it in more intelligent ways.
The company lives by their motto: Data -> Intelligence -> Action.

Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance - key analytics that all feedback into how our AI generates content.

Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy, where he experienced first hand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with HighDimension.IO’s Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye.

In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform to learn deeply about reinforcement learning and supervised learning topics in a commercial setting.
Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean’s List, and received awards such as the Deutsche Bank Artificial Intelligence prize.

http://www.filecondo.com/dl.php?f=Q7b20d1GM92h