Duba Asali
0 ratings
Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4
genuine image
Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4
Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4
Lambar abu: 49261621

Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and

87% of respondents would recommend this to a friend

Lambar abu: 49261621

XAF 59680

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

*All items will import from Ƙasar Amurika US

0 ratings Rubuta bita
A Stock
Ƙasar Amurika US An shigo da shi daga kantin USA
Yi Oda yanzu, a samu nan da Talata, Satumba 22
Secured transactionsecured transaction

Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

Our Top Logistics Partners
  • fedex
  • dhl
Garanti na U-care:
Babu
Zaɓi tsari
fast shipping

Fast
Shipping

free return

Free
Return*

secure packaging

Secure Packaging

100% original products

100% Original Products

pci-dss

PCI DSS Compliance

iso certified

ISO 27001 Certified

paypal payment
visa payment
mastercard payment
Note: Step Down Voltage Transformer required for using electronics products of Ƙasar Amurika US store (110-120). Recommended power converters Saya yanzu.

What Stands Out

Comprehensive Coverage
This edition thoroughly covers deep learning architectures for NLP, offering detailed insights on architectures like GPT-3, ChatGPT, and GPT-4, making it ideal for both beginners and experienced practitioners.
Hands-On Approach
Offers practical exercises and real-world examples using Python and Hugging Face, empowering readers to build, train, and fine-tune models effectively, enhancing their practical understanding of NLP applications.
Updated Technologies
Incorporates the latest advancements in NLP technology, ensuring readers gain current knowledge on state-of-the-art models, preparing them for modern industry challenges and advanced computational techniques.

Bayanin samfur

Shop Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 online at a best price in Chad. 1803247339
  • Consolidates OpenAI’s GPT-3, ChatGPT, GPT-4, and Hugging Face transformers for language tasks
  • Includes a free eBook in PDF format with print or Kindle book purchase
  • Improves productivity with OpenAI’s ChatGPT and GPT-4 for prompt engineering and machine learning models
  • Guides pretraining a BERT-based model from scratch using Hugging Face
  • Provides step-by-step guidance on fine-tuning powerful transformer models, including OpenAI's GPT-3
  • Covers various NLP tasks, machine translations, speech-to-text, text-to-speech, and more
Publisher Packt Publishing
Publication date March 25, 2022
Edition 2nd ed.
Language English
Print length 602 pages
ISBN-10 1803247339
ISBN-13 978-1803247335
Item Weight 2.25 pounds (1.02 kg)
Dimensions 7.5 x 1.36 x 9.25 inches (19.1 x 3.5 x 23.5 cm)

Who Should Buy?

Suitable For
  • AI Enthusiasts

    Individuals keen on understanding deep learning and NLP will find this resource invaluable for hands-on learning.

  • Data Scientists

    Professionals who work with text data can benefit from practical knowledge of transformers in real-world applications.

  • Machine Learning Students

    Students pursuing machine learning courses can effectively apply theories through coding examples and projects presented in the book.

Not Suitable For
  • Beginner Programmers

    Individuals with no programming experience may struggle with the advanced concepts and coding implementations presented.

KWATANCEN ABUN

Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4

Kuna da wata tambaya? Yi taɗi da mu

Tambayoyi & Amsoshi Abokin Ciniki

  • Tambaya: What are transformers in Natural Language Processing?

    Amsa: Transformers are a type of neural network architecture that utilize self-attention mechanisms to process and generate text. They excel at understanding context and relationships within text data, making them ideal for various NLP tasks like translation, sentiment analysis, and text summarization. Unlike traditional models, transformers can handle long-range dependencies within text, allowing for more coherent and contextually appropriate outputs in tasks such as chatbots or automated content generation.
  • Tambaya: How can I build a transformer model for NLP?

    Amsa: Building a transformer model for NLP involves utilizing libraries like Hugging Face’s Transformers along with Python. You start by selecting a pre-trained model as a base, then adapt it for your specific task by fine-tuning on your dataset. This process involves configuring the model architecture, defining training parameters, and using optimizers effectively. By customizing aspects like architecture size or learning rates, you can optimize performance for applications such as text classification or named entity recognition.
  • Tambaya: What does fine-tuning a transformer model involve?

    Amsa: Fine-tuning a transformer model entails adjusting the pre-trained model on a specific dataset relevant to your NLP task. This process includes modifying hyperparameters, such as learning rates and batch sizes, ensuring the model focuses on your specific text data characteristics. Fine-tuning improves the model's accuracy and relevance, making it particularly useful in tasks like sentiment analysis or domain-specific conversational AI, where standard models may not capture the nuances of specialized vocabulary.
  • Tambaya: Which programming language is commonly used for working with transformers?

    Amsa: Python is the most commonly used programming language for working with transformers, especially in the field of Natural Language Processing. The popularity of libraries like Hugging Face’s Transformers simplifies integration and use of transformer models. This allows developers to leverage Python’s extensive ecosystem of data science libraries, making it easier to preprocess data, implement models, and conduct evaluations, ideal for projects involving text generation or chatbots.
  • Tambaya: Can transformers be used for tasks beyond text?

    Amsa: Yes, transformers are versatile and can be adapted for tasks beyond text processing. They have been successfully applied in fields such as image processing and audio analysis, thanks to their ability to learn complex relationships in data. For example, models like Vision Transformers (ViTs) are innovating by applying transformer principles to image classification tasks, showcasing their adaptability and potential in different domains like healthcare imaging or speech recognition.
  • Tambaya: What role does Hugging Face play in using transformers?

    Amsa: Hugging Face serves as a leading platform for developers and researchers working with transformer models. It offers a rich library of pre-trained models that can be easily integrated into various applications. The extensive documentation and active community make it accessible for both beginners and experts. Whether you’re building a chatbot or conducting research in NLP, Hugging Face provides the tools and resources to enhance your project’s effectiveness and speed of development.
  • Tambaya: What are some practical applications of transformers in NLP?

    Amsa: Transformers are employed in a variety of practical applications within NLP. Common use cases include machine translation, where they enable seamless and accurate language translations, and chatbots, which can generate contextually relevant responses in conversations. Additionally, transformers improve text summarization tools and sentiment analysis systems, allowing businesses to glean insights from customer feedback effectively. Their versatility makes them crucial in creating engaging user experiences across different platforms.
  • Tambaya: Is it necessary to have a strong background in ML to work with transformers?

    Amsa: While a solid understanding of machine learning concepts can be beneficial, it is not strictly necessary to work with transformers. Tools such as Hugging Face provide accessible interfaces and extensive tutorials that simplify the process. Users can get started with basic programming knowledge and gradually build their skills through hands-on experience. This opens the door for enthusiasts and professionals from various backgrounds to engage with powerful NLP tools for diverse applications.
  • Tambaya: What are the hardware requirements for training transformer models?

    Amsa: Training transformer models typically requires powerful hardware due to their high computational demands. A compatible GPU is ideal for efficient training, as it significantly speeds up the process compared to CPU-only setups. Depending on your dataset size and model complexity, a machine with 16GB or more of VRAM is recommended. This setup facilitates quicker experimentation and better performance when implementing large-scale NLP applications like language generation or text analytics.
  • Tambaya: Where can I buy Transformers for Natural Language Processing?

    Amsa: You can purchase 'Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face' on Ubuy, which offers a wide range of books in various categories. Ubuy ensures you have access to essential materials that aid in the development of your understanding and application of transformers in NLP, making it a go-to resource for learners and professionals alike.

Neural Networks Editorial Review

Ba a sami sake dubawa na edita ba

Customer Reviews & Ratings

1 Ƙimar da abokan ciniki suka bayar
  • 5 Tauraruwa
    100%
  • 4 Tauraruwa
    0%
  • 3 Tauraruwa
    0%
  • 2 Tauraruwa
    0%
  • 1 Tauraruwa
    0%

Yi bitar akan wannan Samfurin

Faɗan wa sauran Abokan ciniki ra'ayin ka

Platform Trust & Buyer Confidence

trustpilot logo
4.2/5 9477 reviews
Read reviews
JK
Jasmin
Verified buyer

“Great products and very good service: very easy and very fast international delivery.”

9 September 2026 · via Trustpilot
AG
Anke
Verified buyer

“Wonderful online shopping experience, smooth transaction from the start. Payment method works conveniently and delivery is unexpectedly fast and reliable. You go the extra mile for service. What makes this even more amazing, you deliver to Namibia. I will remain a happy Ubuy customer and will increase my purchases for sure! Thank you!”

10 September 2026 · via Trustpilot
H
Hazel
Verified buyer

“Very easy to find the products what you need, and so fast delivery, that’s why I highly recommended to others costumers to used ubuy.”

10 September 2026 · via Trustpilot
O
Opaleye
Verified buyer

“I received exactly what I ordered I was skeptical about your site because that was my first time to order. But the order came timely and neatly packaged. I was not disappointed. Thank you.”

11 September 2026 · via Trustpilot
AC
Adele
Verified buyer

“Easy to find and order what you want on the website. Delivery is quick to the UK”

8 September 2026 · via Trustpilot
Biyan Kuɗi Amintaccen Global Delivery Easy Returns Genuine Products

Product Price History

Sanarwa mai amfani

  • Iyakoki: Don Abubuwan da aka yi sufurin su daga ƙasashen waje, a lura da cewa garanti ɗin mai ƙira ba lallai ya yi aiki ba; wajan neman taimakon mai ƙira ba lallai ya samu ba; kuma Littafin Sanin yanda abu yake aiki, hanyoyin tsaro da umarni ba lallai ya kasance a yaren ƙasar mai siya ba; Samfurin kaya (da sauran kayan haɗi) ba lallai ne an ƙera su a bisa tsarin ƙasar da za a kaya kayan ba, da ƙayyadaddun bayanai, ko dokar yin alama ko laƙabi; kuma ba lallai bane samfuran kayan su dace da ma'aunin wutar lantarki na voltage ɗin kasar da sauran dokokin ƙasa na wutar lantarki (wanda za'a buƙaci amfani da na'urar adafta ko na'urar canza launi idan ya dace). Mai karɓar kaya shi/ita ke da alhakin tabbatar da cewa samfurin da aka siya za'a iya shigo da shi ƙasar da za'a kai a bisa dokar ƙasar. A yayin yin oda daga Ubuy ko masu alaƙa da su, mai karɓar oda ne mai shigo da kaya, kuma dole ya/ta tabbarar da cewa ya/ta bi duka dokokin ƙasar da za'a kai kayan.
  • Ba dukkan abubuwan da aka saka a kan Ubuy bane na sayar wa, don Ubuy wajen bincike ne na duk duniya. Duk wani Samfurin abu yana da dokokin shige da fice na ƙasashe da kuma dokokin siye da sayar wa.

XAF 59680

Yi Oda yanzu, a samu nan da Talata, Satumba 22

QTY:

Secured transactionsecured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners
  • fedex
  • dhl
Fastest cross-border delivery

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns *, and secure packaging on every order.