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Essential Skills in Text Classification, Sentiment Analysis, TensorFlow Techniques, and Model Building

What you will learn

Understand the fundamentals of NLP and its applications in technology and daily life.

Gain proficiency in using TensorFlow Text for building and optimizing NLP models.

Master various NLP model architectures including RNNs, CNNs, and Transformers.

Develop practical skills in text classification, sentiment analysis, and data preprocessing.

Learn to preprocess text data efficiently, including tokenization, normalization, and vectorization techniques.

Apply NLP techniques to real-world problems, creating models for sentiment analysis and text classification.

Explore advanced topics in NLP such as sequence-to-sequence models, attention mechanisms, and transfer learning.

Evaluate and improve NLP model performance using metrics like accuracy, precision, recall, and F1 score.

Understand how to handle challenges in NLP, including dealing with ambiguity and context in language.

Acquire skills in leveraging pre-trained models like BERT and GPT for NLP tasks, enhancing model efficiency.

Develop an understanding of linguistic concepts crucial for NLP, such as syntax, semantics, and pragmatics.

Description

Dive into the transformative world of Natural Language Processing (NLP) with our comprehensive course designed to take you from a curious beginner to a proficient practitioner. In the era where machines understand and interpret human language, our course stands as a beacon for those eager to master the art of teaching computers to process, analyze, and generate language just like humans do. Whether you’re aspiring to innovate in tech, looking to harness the power of AI in your projects, or simply fascinated by the intersection of linguistics and technology, this course is your gateway to the vast possibilities of NLP.

Starting with the basics, we introduce you to the fascinating world of NLP, laying a strong foundation with clear explanations of core concepts and their applications in everyday technology. From search algorithms that predict your queries to virtual assistants that understand your requests, you’ll gain insights into how NLP powers the technology that makes our lives more convenient and connected. No prior experience in NLP or TensorFlow Text is necessary, as we guide you step-by-step through the learning process, ensuring that beginners find a comfortable starting point, while more experienced learners can deepen their expertise.

As you progress, the course delves into TensorFlow Text, Google’s powerful library specifically designed for NLP tasks. You’ll learn to leverage its capabilities to preprocess text data, build sophisticated NLP models, and solve real-world problems. Through hands-on projects and practical examples, you’ll gain experience in text classification, sentiment analysis, and more, applying these skills to create AI applications that can understand and generate human language.


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Our curriculum covers a wide range of model architectures, including Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and the revolutionary Transformers. By exploring these models, you’ll understand their applications and strengths, learning how to choose the right architecture for your NLP project. Moreover, we dive into advanced topics such as sequence-to-sequence models and attention mechanisms, preparing you for cutting-edge developments in the field.

What sets this course apart is not just the breadth and depth of the content but also the practical approach to learning. You’ll work on real-world datasets, tackle actual NLP challenges, and build a portfolio of projects that demonstrate your new skills. Whether you’re a software developer, a data scientist, a student, or an entrepreneur, you’ll find valuable knowledge and skills that can be applied to your career or personal projects.

Join a community of learners who are passionate about unlocking the potential of NLP to change the way we interact with technology. With flexible online access, you can learn at your own pace and on your own schedule, supported by experts and a vibrant community. Don’t miss the opportunity to transform your understanding of NLP and open the door to a world of innovation and opportunity. Enroll in our course today and start your journey to becoming an NLP expert!

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Content

Introduction

Welcome and Course Overview
Why Learn NLP?
Introduction to TensorFlow Text

The Basics of Natural Language Processing

What is NLP?
The History and Evolution of NLP
Key Applications of NLP
Understanding Natural Language Processing (NLP)

Linguistics for NLP

Introduction to Syntax
Exploring Semantics
Syntax & Semantics
The Role of Morphology
Understanding Pragmatics
Morphology & Pragmatics

Challenges in NLP

Dealing with Ambiguity
Context and Nuance in NLP
Figurative Language and Idioms

Deep Dive into TensorFlow Text

Why TensorFlow Text?
Core Components of TensorFlow Text
TensorFlow Basics
TensorFlow Basics (Examples)

Preprocessing Text Data with TensorFlow Text

Tokenization Techniques
Tokenization Techniques (Examples)
Text Normalization
Text Normalization (Examples)
Stemming and Lemmatization
Stemming and Lemmatization (Examples)

Vectorization and Embeddings

The Process of Vectorization
The Process of Vectorization (Examples)
Introduction to Word Embeddings
Introduction to Word Embeddings (Examples)

Understanding NLP Models

Overview of NLP Model Architectures
RNNs, LSTMs, and GRUs for NLP
RNNs, LSTMs, and GRUs for NLP (Examples)
CNNs and Transformers for NLP
CNNs and Transformers for NLP (Examples)

Sentiment Analysis with TensorFlow Text

Introduction to Sentiment Analysis
Building a Sentiment Analysis Model
Building a Sentiment Analysis Model (Demo)
Analyzing Model Outputs

Text Classification with with TensorFlow Text

Principles of Text Classification
Building a Text Classification Model
Building a Text Classification Model (Demo)