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Hugging Face for Natural Language Processing (NLP) Training LONDON | Hugging Face for Natural Language Processing (NLP) Training COURSES UK | Weekend | Evening | Online

Professional certification in Programming

Hugging Face for Natural Language Processing (NLP) Training

Our IT training courses are developed with industry-standards and career-focused technologies.


Speak to an advisor
Award:
Certification
Duration & Study Mode:
Full time, Part-time, Evening and Weekends, Virtual online
Location:
London, Flexible online
Duration: 4 days

In the world of Natural Language Processing (NLP), Hugging Face has emerged as a powerful platform that democratizes access to state-of-the-art NLP models and tools. This comprehensive course, “Hugging Face for Natural Language Processing (NLP) Training,” is designed to equip you with the knowledge and skills needed to harness the full potential of Hugging Face’s transformers library and related resources for a wide range of NLP tasks. Whether you’re a data scientist, machine learning engineer, or NLP enthusiast, this course will empower you to leverage cutting-edge models and techniques effectively.

Prerequisites

  • Basic knowledge of Python programming.
  • Familiarity with machine learning and deep learning concepts is helpful but not mandatory.
  • No prior experience with Hugging Face is required, as the course covers the platform comprehensively.

What will you gain after this course

  • Introduction to Hugging Face: Gain a foundational understanding of Hugging Face, its mission, and its role in the NLP landscape.
  • Exploration of Transformers: Dive into the transformers library, explore pre-trained models, and learn how to fine-tune them for specific NLP tasks.
  • NLP Fundamentals: Build a strong foundation in NLP concepts, including tokenization, word embeddings, attention mechanisms, and more.
  • Hands-on Model Training: Develop the skills to train and fine-tune NLP models on custom datasets using Hugging Face’s easy-to-use API.
  • Transfer Learning: Understand the power of transfer learning and how to adapt pre-trained models to your specific NLP applications.
  • Model Deployment: Learn how to deploy Hugging Face models in various production environments, including web applications and cloud platforms.
  • Advanced NLP Tasks: Explore advanced NLP tasks such as text generation, question answering, sentiment analysis, and language translation using Hugging Face models.
  • Model Interpretability: Discover techniques for interpreting and explaining the predictions of NLP models, including attention visualization and saliency maps.
  • Real-world Applications: Apply your NLP skills to real-world projects, including chatbots, sentiment analysis systems, and text summarization applications.

Jobs you can get
with a Natural Language Processing (NLP) Fundamentals with Python Certification

  • Natural Language Processing Specialist
  • Senior Data Scientist – Natural Language Processing
  • Application Developer – Natural Language Processing
  • Data Language Engineer
  • Senior Associate, Analytics – Natural Language Processing
  • Machine Learning Engineer

Corporate Group Training

  • Customized Training
  • Onsite / Virtual
  • Instructor-led Delivery
  • For small to large groups

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Select your preferred training delivery mode

Who is this certification for?

  • Data Scientists and Analysts
  • Machine Learning Engineers
  • NLP Practitioners
  • Software Developers interested in NLP
  • Anyone looking to enhance their NLP skills using Hugging Face




Group-Icon2
Small Groups

With small groups of students, our instructors can work closely with each student.

Schedule
Flexible Class Schedules

Our class schedules are flexible on weekdays, weekend, or evenings to suit your schedule.

Instructors
Experienced Instructors

Our instructors follow a modified are personalized approach to engage students during class

Lab-Facilities
Hi-Tech Lab Facilities

Our students can access our lab facilities anytime for practical experience during and after studies.

Syllabus

Introduction

  • Overview of NLP and its applications
  • Introduction to Hugging Face and its key features

Setting up a working environment

  • Installing and configuring Hugging Face

Understanding the Hugging Face Transformers library and Transformer Models

  • Exploring the Transformers library structure and functionalities
  • Overview of various Transformer models available in Hugging Face

Utilizing Hugging Face Transformers

  • Loading and using pretrained models
  • Applying Transformers for various NLP tasks

Fine-Tuning a Pretrained Model

  • Preparing a dataset for fine-tuning
  • Fine-tuning a Transformer model on a specific task

Sharing Models and Tokenizers

  • Exporting and sharing trained models
  • Utilizing tokenizers for text processing

Exploring Hugging Face Datasets Library

  • Overview of the Datasets library in Hugging Face
  • Accessing and utilizing pre-existing datasets

Exploring Hugging Face Tokenizers Library

  • Understanding tokenization techniques and their importance
  • Leveraging tokenizers from Hugging Face

Carrying out Classic NLP Tasks

  • Implementing common NLP tasks using Hugging Face
  • Text classification, sentiment analysis, named entity recognition, etc.

Leveraging Transformer Models for Addressing Tasks in Speech Processing and Computer Vision

  • Extending the use of Transformers beyond text-based tasks
  • Applying Transformers for speech and image-related tasks

Troubleshooting and Debugging

  • Common issues and challenges in working with Hugging Face
  • Techniques for troubleshooting and debugging

Building and Sharing Your Model Demos

  • Designing and creating interactive model demos
  • Sharing and showcasing your models effectively

Summary and Next Steps

  • Recap of key concepts and techniques learned
  • Guidance on further exploration and resources for continued learning





When would you like to start?

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