Boost the Model. Deepen the Intelligence. Ship to Production.

Key Features
● Get a free one-month digital subscription to www.avaskillshelf.com.
● Hands-on LightGBM and TensorFlow mastery covering gradient boosting, neural networks, and hybrid model architectures.
● Production-ready MLOps pipelines with Docker, Kubernetes, CI/CD automation, and cloud deployment for enterprise AI.
● Explainable AI implementation using SHAP, LIME, and TensorBoard alongside ChatGPT and GitHub Copilot for accelerated development.

Book Description
Build Models That Win on Accuracy—and Systems That Win in Production.

Machine Learning (ML) practitioners who can combine gradient boosting with deep learning, and deploy the results to production are the engineers solving the hardest problems in enterprise AI. Ultimate Machine Learning with LightGBM Using TensorFlow provides a practical, end-to-end guide for building intelligent, scalable, and production-ready ML systems using two of the most powerful frameworks in modern AI.

You begin with ML fundamentals and ensemble methods, then advance through XGBoost, LightGBM, and TensorFlow neural networks before combining them into hybrid architectures that deliver performance. Each chapter integrates hands-on Python examples, feature engineering, hyperparameter tuning, explainable AI using SHAP, LIME, and TensorBoard, with AI-assisted development throughout using ChatGPT and GitHub Copilot.

The final section addresses production deployment, covering MLOps practices, Docker, Kubernetes, CI/CD pipelines, and cloud deployment. Thus, by the end of the book, you will design, optimize, deploy, and manage enterprise-grade ML applications with technical depth and practical confidence.

What you will learn
● Build high-performance ML models using LightGBM and TensorFlow for real-world business applications.
● Design hybrid AI architectures combining gradient boosting and deep learning for complex problem solving.
● Optimise model accuracy through feature engineering, hyperparameter tuning, and explainable AI methods.
● Develop production-ready ML pipelines using MLOps, Docker, Kubernetes, and automated CI/CD practices.
● Implement end-to-end ML workflows from data preparation through cloud deployment with production confidence.
● Leverage ChatGPT and GitHub Copilot to accelerate machine learning development and debugging workflows.

Table of Contents
1. Introduction to ML Landscape
2. Ensemble Methods and Tree-Based Models
3. XGBoost and Gradient Boosting
4. Introduction to LightGBM
5. Data Preparation and Feature Engineering for LightGBM
6. Hyperparameter Tuning for Optimal Performance
7. Practical Applications and Interpretability
8. Introduction to TensorFlow
9. Crafting and Training a Neural Network
10. Efficient Data Pipelines with tf.data
11. Building Hybrid and Stacked Models
12. Seamless Integration with tf.data
13. Advanced Topics and Real-World Case Studies
14. A Final Project
15. The Future of ML and Further Learning
Index

"Synopsis" may belong to another edition of this title.

preigu

Osnabrück, Germany

5-star seller

AbeBooks seller since August 5, 2024

Shipping rates from Germany to U.S.A.

Item	60 to 60 business days	60 to 60 business days
First item	£ 59.14	£ 59.14

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

Paypal

Store description

preigu betreibt einen Onlineversandhandel mit über 1 Mio. Produkten in verschiedenen Sortimenten. Das Kernsortiment besteht aus Büchern, Medien und Spielwaren. Ein gelungenes Einkaufserlebnis ist das Ziel einer jeden Bestellung bei preigu, denn der Kunde und seine Zufriedenheit stehen an erster Stelle. preigu setzt daher auf einen kompetenten Kundenservice, funktionierende Prozesse und schnelle Reaktion.

Specialty

Bücher, Spielwaren

Seller's business information

preigu GmbH & Co. KG

Lengericher Landstraße 19
Osnabrück, Germany 49078

Contact sellerView this seller's itemsView seller's storefront

Terms of sale

About Us

Legal website operator identification:

preigu GmbH & Co. KG
Lengericher Landstr. 19
49078 Osnabrück
Germany

Telephone: +49 (0) 541 / 580 72 84
Email: mail@preigu.de

VAT No: DE 455 380 498
AG Osnabrück - HRA 209647

PhG: preigu Verwaltung GmbH
AG Osnabrück - HRB 221793
CEO: Ansas Meyer

We are neither willing nor obliged to participate in dispute resolution proceedings before consumer arbitration boards.

We are a member of the initiative "FairCommerce" since 30.11.2016.
For more information, see: https://www.haendlerbund.de/de/haendlerbund/interessenvertretung/faircommerce

Right of withdrawal

Instructions for revocation

Right of withdrawal for the sale of goods

Revocation right for consumers
(A ‘consumer' is any natural person who concludes a legal transaction which, to an overwhelming extent, cannot be attributed to either his commercial or independent professional activities.)

Instructions for revocation

Revocation right
You have the right to revoke this contract within 14 days without specifying any reasons.
The revocation period is 14 days with effect from the day,

on which you or a third party nominated by you, which is not the carrier, had taken possession of the products, provided you had ordered one or more products within the scope of a standard order and this/these product/products is/are delivered uniformly;
on which you or a third party nominated by you, which is not the carrier, had taken possession of the last product, provided you had ordered several products within the scope of a standard order and these products are delivered separately;
on which you or a third party nominated by you, which is not the carrier, had taken possession of the last part delivery or the last unit, provided you had ordered a product, which is delivered in several part deliveries or units;

To exercise your right of withdrawal, you must inform us (preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, Telephone number: +49 (0) 541 / 580 72 84, E-Mail address: mail@preigu.de) by means of a clear declaration (e.g. a letter sent by post, or an e-mail) of your decision to withdraw from this contract. You can use the attached model withdrawal form for this purpose, which is, however, not mandatory.

You can also exercise your right of withdrawal online by clicking on a button labelled accordingly (such as ‘Withdraw from contract' or similar) on the AbeBooks/ZVAB website. If you use this online function, you will immediately receive a confirmation of receipt on a durable medium (e.g. via email) containing information on the content of the withdrawal notice, as well as the date and time of its receipt.

In order to safeguard the revocation period, it is sufficient that you send the notification about the exercise of the revocation right before the expiry of the revocation period.

Consequences of the revocation

If you revoke this contract, we shall repay all the payments, which we received from you, including the delivery costs (with the exception of additional costs, which arise from that fact that you selected a form of delivery other than the most reasonable standard delivery offered by us), immediately and at the latest within 14 days from the day on which we received the notification about the revocation of this contract from you. We use the same means of payment, which you had originally used during the original transaction, for this repayment unless expressly agreed otherwise with you; you will not be charged any fees owing to this repayment.

We can refuse the repayment until the products are returned to us or until you have furnished evidence that you have sent the products back to us, depending on whichever is earlier.

You must return or transfer the products to us immediately and, in any case, at the latest within 14 days with effect from the day on which you inform us of the revocation of this contract. The deadline is maintained if you send the products before the expiry of the 14 day deadline.

You bear the direct costs for returning the products.

You must pay for any depreciation of the products only if this depreciation can be attributed to any handling with you that was not necessary for checking the condition, features and functionality of the products.

Criteria for exclusion or expiry

The revocation right is not available for contracts

for delivery of products, which are not prefabricated and for whose manufacturing an individual selection or stipulation by the consumer is important or which are clearly tailored to the personal requirements of the consumer;
for delivery of products, which can spoil quickly or whose use-by date would be exceeded quickly;
for delivery of alcoholic drinks, whose price was agreed at the time of concluding the contract, which however can be delivered 30 days after the conclusion of the contract at the earliest and whose current value depends on the fluctuations in the market, on which the entrepreneur has no influence;
for delivery of newspapers, periodicals or magazines with the exception of subscription contracts. The revocation right expires prematurely in case of contracts
for delivery of sealed products, which are not suitable for return for reasons of health protection or hygiene if their seal has been removed after the delivery;
for delivery of products if they have been mixed inseparably with other goods after the delivery, owing to their condition;
for delivery of sound or video recording or computer software in a sealed package if the seal has been removed after the delivery.

Specimen - revocation form

(If you wish to revoke the contract, please fill up this form and send it back to us.)

To preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, Email address: mail@preigu.de :
I/we () herewith revoke the contract concluded by me/ us () regarding the purchase of the following products ()/
the provision of the following service ()
Ordered on ()/ received on ()
Name of the consumer(s)
Address of the consumer(s)
Signature of the consumer(s) (only in case of a notification on paper)
Date

(*) Cross out the incorrect option.

Ultimate Machine Learning with LightGBM Using TensorFlow

Item description from seller

Bibliographic details

Synopsis