Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
Overview
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. Key Features Third edition of the bestselling, widely acclaimed Python machine learning book Clear and intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices Book Description Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents. This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments. What you will learn Master the frameworks, models, and techniques that enable machines to 'learn' from data Use scikit-learn for machine learning and TensorFlow for deep learning Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more Build and train neural networks, GANs, and other models Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who This Book Is For If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.Description
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- Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Item may but the dust cover may be missing. Pages may include limited notes and highlighting, but the text cannot be obscured or unreadable.
Note: Some electronic material access codes are valid only for one user. For this reason, used books, including books listed in the Used – Like New condition, may not come with functional electronic material access codes.
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Depending on where you live, the time it may take for your exchanged product to reach you, may vary.
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Categories
Overview
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. Key Features Third edition of the bestselling, widely acclaimed Python machine learning book Clear and intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices Book Description Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents. This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments. What you will learn Master the frameworks, models, and techniques that enable machines to 'learn' from data Use scikit-learn for machine learning and TensorFlow for deep learning Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more Build and train neural networks, GANs, and other models Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who This Book Is For If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.Description
Condition Guidelines
Books - New and Used
The following guidelines apply to books:
- New: A brand-new copy with cover and original protective wrapping intact. Books with markings of any kind on the cover or pages, books marked as "Bargain" or "Remainder," or with any other labels attached, may not be listed as New condition.
- Used - Good: All pages and cover are intact (including the dust cover, if applicable). Spine may show signs of wear. Pages may include limited notes and highlighting. May include "From the library of" labels. Shrink wrap, dust covers, or boxed set case may be missing. Item may be missing bundled media.
- Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Item may but the dust cover may be missing. Pages may include limited notes and highlighting, but the text cannot be obscured or unreadable.
Note: Some electronic material access codes are valid only for one user. For this reason, used books, including books listed in the Used – Like New condition, may not come with functional electronic material access codes.
Shipping & Delivery
Shipping Fees
- Stevens Books offers FREE SHIPPING everywhere in the United States for ALL non-book orders, and $3.99 for each book.
- Packages are shipped from Monday to Friday.
- No additional fees and charges.
Delivery Times
The usual time for processing an order is 24 hours (1 business day), but may vary depending on the availability of products ordered. This period excludes delivery times, which depend on your geographic location.
Estimated delivery times:
- Standard Shipping: 5-8 business days
- Expedited Shipping: 3-5 business days
Shipping method varies depending on what is being shipped.
Tracking
All orders are shipped with a tracking number. Once your order has left our warehouse, a confirmation e-mail with a tracking number will be sent to you. You will be able to track your package at all times.
Damaged Parcel
If your package has been delivered in a PO Box, please note that we are not responsible for any damage that may result (consequences of extreme temperatures, theft, etc.).
If you have any questions regarding shipping or want to know about the status of an order, please contact us or email to support@stevensbooks.com.
Returns & Refunds
You may return most items within 30 days of delivery for a full refund.
To be eligible for a return, your item must be unused and in the same condition that you received it. It must also be in the original packaging.
Several types of goods are exempt from being returned. Perishable goods such as food, flowers, newspapers or magazines cannot be returned. We also do not accept products that are intimate or sanitary goods, hazardous materials, or flammable liquids or gases.
Additional non-returnable items:
- Gift cards
- Downloadable software products
- Some health and personal care items
To complete your return, we require a tracking number, which shows the items which you already returned to us.
There are certain situations where only partial refunds are granted (if applicable)
- Book with obvious signs of use
- CD, DVD, VHS tape, software, video game, cassette tape, or vinyl record that has been opened
- Any item not in its original condition, is damaged or missing parts for reasons not due to our error
- Any item that is returned more than 30 days after delivery
Items returned to us as a result of our error will receive a full refund,some returns may be subject to a restocking fee of 7% of the total item price, please contact a customer care team member to see if your return is subject. Returns that arrived on time and were as described are subject to a restocking fee.
Items returned to us that were not the result of our error, including items returned to us due to an invalid or incomplete address, will be refunded the original item price less our standard restocking fees.
If the item is returned to us for any of the following reasons, a 15% restocking fee will be applied to your refund total and you will be asked to pay for return shipping:
- Item(s) no longer needed or wanted.
- Item(s) returned to us due to an invalid or incomplete address.
- Item(s) returned to us that were not a result of our error.
You should expect to receive your refund within four weeks of giving your package to the return shipper, however, in many cases you will receive a refund more quickly. This time period includes the transit time for us to receive your return from the shipper (5 to 10 business days), the time it takes us to process your return once we receive it (3 to 5 business days), and the time it takes your bank to process our refund request (5 to 10 business days).
If you need to return an item, please Contact Us with your order number and details about the product you would like to return. We will respond quickly with instructions for how to return items from your order.
Shipping Cost
We'll pay the return shipping costs if the return is a result of our error (you received an incorrect or defective item, etc.). In other cases, you will be responsible for paying for your own shipping costs for returning your item. Shipping costs are non-refundable. If you receive a refund, the cost of return shipping will be deducted from your refund.
Depending on where you live, the time it may take for your exchanged product to reach you, may vary.
If you are shipping an item over $75, you should consider using a trackable shipping service or purchasing shipping insurance. We don’t guarantee that we will receive your returned item.
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