Описание: Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and generative adversarial networks. Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of Deep Learning with Python explains the best practices in taking these models to production with PyTorch. What You'll Learn
Review machine learning fundamentals such as overfitting, underfitting, and regularization.
Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automatic differentiation, and stochastic gradient descent.
Apply in-depth linear algebra with PyTorch
Explore PyTorch fundamentals and its building blocks
Work with tuning and optimizing models
Who This Book Is For Beginners with a working knowledge of Python who want to understand Deep Learning in a practical, hands-on manner.
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Do you want to know everything about Data science?
This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful
There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.
Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.
The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.
There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.
This book covers:
What Is Data Science?
How Can I Use Data Science?
The Best Python Libraries for Data Science
Setting Up Your Virtual Environments for Data Science
The Importance of the NumPy Arrays
Gathering and Collecting Your Data
Loading and Preparing Your Dataset
Data Mining
Completing the Data Analysis
How Machine Learning Can Help
How to Work with Data Visualization
Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.
Описание: This book will get you to grips with the Spark Python API. You`ll explore how Python can be used with Spark to build scalable and reliable data-intensive applications.
Chapter Goal: Introduce readers to the PySpark environment, walk them through steps to setup the environment and execute some basic operations
Number of pages: 20
Subtopics:
1. Setting up your environment & data
2. Basic operations
Chapter 2: Basic Statistics and Visualizations
Chapter Goal: Introduce readers to predictive model building framework and help them acclimate with basic data operations
Number of pages: 30
Subtopics:
1. Basic Statistics
2. data manipulations/feature engineering
3. Data visualizations
4. Model building framework
Chapter 3: Variable Selection
Chapter Goal: Illustrate the different variable selection techniques to identify the top variables in a dataset and how they can be implemented using PySpark pipelines
Number of pages: 40
Subtopics:
1. Principal Component Analysis
2. Weight of Evidence & Information Value
3. Chi square selector
4. Singular Value Decomposition
5. Voting based approach
Chapter 4: Introduction to different supervised machine algorithms, implementations & Fine-tuning techniques
Chapter Goal: Explain and demonstrate supervised machine learning techniques and help the readers to understand the challenges, nuances of model fitting with multiple evaluation metrics
Number of pages: 40
Subtopics:
1. Supervised:
- Linear regression
- Logistic regression
- Decision Trees
- Random Forests
- Gradient Boosting
- Neural Nets
- Support Vector Machine
- One Vs Rest Classifier
- Naive Bayes
2. Model hyperparameter tuning:
- L1 & L2 regularization
- Elastic net
Chapter 5: Model Validation and selecting the best model
Chapter Goal: Illustrate the different techniques used to validate models, demonstrate which technique should be used for a particular model selection task and finally pick the best model out of the candidate models
Number of pages: 30
Subtopics:
1. Model Validation Statistics:
- ROC
- Accuracy
- Precision
- Recall
- F1 Score
- Misclassification
- KS
- Decile
- Lift & Gain
- R square
- Adj
Автор: Mishra Raju Kumar, Raman Sundar Rajan Название: Pyspark SQL Recipes: With Hiveql, Dataframe and Graphframes ISBN: 148424334X ISBN-13(EAN): 9781484243343 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL code.
PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You’ll also discover how to solve problems in graph analysis using graphframes.
On completing this book, you’ll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases.
What You Will Learn
Understand PySpark SQL and its advanced featuresUse SQL and HiveQL with PySpark SQLWork with structured streamingOptimize PySpark SQL Master graphframes and graph processing
Who This Book Is For
Data scientists, Python programmers, and SQL programmers.
Описание: If you are a developer looking to build machine learning models without spending months and years learning machine learning prerequisites, look no further than AutoML. This practical and concise guide will show you how to build automated models for regression and classification, both with traditional algorithms and neural networks.
Описание: The Data Science Workshop equips you with the basic skills you need to start working on a variety of data science projects. You`ll work through the essential building blocks of a data science project gradually through the book, and then put all the pieces together to consolidate your knowledge and apply your learnings in the real world.
Inside this book you will find all the basic notions to start with Python and all the programming concepts to build machine learning models. With our proven strategies you will write efficient Python codes in less than a week!
Описание: Equipped with the latest updates, this third edition of Python Machine Learning By Example provides a comprehensive course for ML enthusiasts to strengthen their command of ML concepts, techniques, and algorithms.
Описание: Are you completely new to Python Programming or do you want to expand your knowledge in the incredible world of Machine Learning?
If you would like to start Programming or learn about Machine Learning and its algorithms but may seem to be a struggle, don't worry Thanks to this complete guide with practical projects and examples you will finally solve your problems
These 2 Books in 1 will teach you fundamental and advance information to master the easiest Programming language, Artificial Intelligence, Data Science and Machine Learning.
Avoid the main mistakes everybody makes and stop waste your precious time and money in expensive online courses.
This is what you will find in this step-by-step guide:
Why Python and Machine Learning are a successful combo
The secrets of the Machine Learning's Success
The Best Trick and practice for Python Programming
... and that's not all
The Importance of Artificial Intelligence nowadays
Solutions for Small Businesses Using Data Science
The best Algorithms to use
...and much more
Take advantage of this Guide and discover this fantastic world
What are you waiting for? Press the Buy-Now button and get started
Описание: Imagine a world where you can make a computer program learn for itself? What if you were able to create any kind of program that you wanted, even as a beginner programmer, without all of the convoluted codes and other information that makes your head spin?
Описание: Are you completely new to Python Programming or do you want to expand your knowledge in the incredible world of Machine Learning?
If you would like to start Programming or learn about Machine Learning and its algorithms but may seem to be a struggle, don't worry Thanks to this complete guide with practical projects and examples you will finally solve your problems
These 2 Books in 1 will teach you fundamental and advance information to master the easiest Programming language, Artificial Intelligence, Data Science and Machine Learning.
Avoid the main mistakes everybody makes and stop waste your precious time and money in expensive online courses.
This is what you will find in this step-by-step guide:
Why Python and Machine Learning are a successful combo
The secrets of the Machine Learning's Success
The Best Trick and practice for Python Programming
... and that's not all
The Importance of Artificial Intelligence nowadays
Solutions for Small Businesses Using Data Science
The best Algorithms to use
...and much more
Take advantage of this Guide and discover this fantastic world
What are you waiting for? Press the Buy-Now button and get started
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