Deep Learning for Beginners: 2 in 1
2 books in 1! This is the bundle of two successful books in the market.
Book 1: In "Deep Learning for Beginners: A comprehensive introduction of deep learning fundamentals for beginners to understanding frameworks, neural networks, large datasets, and creative applications with ease" you will learn:
¿ Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues.
¿ The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook.
¿ The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders.
¿ The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity.
¿ And much more...
Book 2: In "Data Science from Scratch: The #1 Data Science Guide for Everything A Data Scientist Needs to Know: Python, Linear Algebra, Statistics, Coding, Applications, Neural Networks, and Decision Trees" you will learn:
¿ In depth information about what data science is and why it is important.
¿ The prerequisites you will need to get started in data science.
¿ What it means to be a data scientist.
¿ The roles that hacking and coding play in data science.
¿ The different coding languages that can be used in data science.
¿ Why python is so important.
¿ How to use linear algebra and statistics.
¿ The different applications for data science.
¿ How to work with the data through munging and cleaning
¿ And much more...
Get your copy of these fantastic guides to master state-of-the-art, deep learning algorithms and their implementation!
1142809727
Book 1: In "Deep Learning for Beginners: A comprehensive introduction of deep learning fundamentals for beginners to understanding frameworks, neural networks, large datasets, and creative applications with ease" you will learn:
¿ Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues.
¿ The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook.
¿ The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders.
¿ The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity.
¿ And much more...
Book 2: In "Data Science from Scratch: The #1 Data Science Guide for Everything A Data Scientist Needs to Know: Python, Linear Algebra, Statistics, Coding, Applications, Neural Networks, and Decision Trees" you will learn:
¿ In depth information about what data science is and why it is important.
¿ The prerequisites you will need to get started in data science.
¿ What it means to be a data scientist.
¿ The roles that hacking and coding play in data science.
¿ The different coding languages that can be used in data science.
¿ Why python is so important.
¿ How to use linear algebra and statistics.
¿ The different applications for data science.
¿ How to work with the data through munging and cleaning
¿ And much more...
Get your copy of these fantastic guides to master state-of-the-art, deep learning algorithms and their implementation!
Deep Learning for Beginners: 2 in 1
2 books in 1! This is the bundle of two successful books in the market.
Book 1: In "Deep Learning for Beginners: A comprehensive introduction of deep learning fundamentals for beginners to understanding frameworks, neural networks, large datasets, and creative applications with ease" you will learn:
¿ Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues.
¿ The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook.
¿ The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders.
¿ The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity.
¿ And much more...
Book 2: In "Data Science from Scratch: The #1 Data Science Guide for Everything A Data Scientist Needs to Know: Python, Linear Algebra, Statistics, Coding, Applications, Neural Networks, and Decision Trees" you will learn:
¿ In depth information about what data science is and why it is important.
¿ The prerequisites you will need to get started in data science.
¿ What it means to be a data scientist.
¿ The roles that hacking and coding play in data science.
¿ The different coding languages that can be used in data science.
¿ Why python is so important.
¿ How to use linear algebra and statistics.
¿ The different applications for data science.
¿ How to work with the data through munging and cleaning
¿ And much more...
Get your copy of these fantastic guides to master state-of-the-art, deep learning algorithms and their implementation!
Book 1: In "Deep Learning for Beginners: A comprehensive introduction of deep learning fundamentals for beginners to understanding frameworks, neural networks, large datasets, and creative applications with ease" you will learn:
¿ Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues.
¿ The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook.
¿ The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders.
¿ The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity.
¿ And much more...
Book 2: In "Data Science from Scratch: The #1 Data Science Guide for Everything A Data Scientist Needs to Know: Python, Linear Algebra, Statistics, Coding, Applications, Neural Networks, and Decision Trees" you will learn:
¿ In depth information about what data science is and why it is important.
¿ The prerequisites you will need to get started in data science.
¿ What it means to be a data scientist.
¿ The roles that hacking and coding play in data science.
¿ The different coding languages that can be used in data science.
¿ Why python is so important.
¿ How to use linear algebra and statistics.
¿ The different applications for data science.
¿ How to work with the data through munging and cleaning
¿ And much more...
Get your copy of these fantastic guides to master state-of-the-art, deep learning algorithms and their implementation!
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Deep Learning for Beginners: 2 in 1
Deep Learning for Beginners: 2 in 1
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Product Details
| BN ID: | 2940178351543 |
|---|---|
| Publisher: | Author's Republic |
| Publication date: | 12/02/2022 |
| Edition description: | Unabridged |
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