Nlp With Tensorflow Text: Mastering Ai Powered Text Analysis

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

What you'll 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.

Requirements

Basic understanding of Python programming: Familiarity with Python syntax and basic programming concepts is essential for following the code examples and exercises.

No prior experience with NLP or TensorFlow Text is required: This course is designed to introduce learners to NLP and TensorFlow Text from the ground up, making it suitable for beginners in the field.

(Optional) Fundamental knowledge of machine learning concepts: A grasp of basic machine learning principles, such as training/testing datasets, supervised vs. unsupervised learning, and model evaluation, will be helpful.

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.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!

Overview

Lecture 0 Welcome and Course Overview

Lecture 0 Why Learn NLP?

Lecture 0 Introduction to TensorFlow Text

Section 1: The Basics of Natural Language Processing

Lecture 1 What is NLP?

Lecture 2 The History and Evolution of NLP

Lecture 3 Key Applications of NLP

Section 2: Linguistics for NLP

Lecture 4 Introduction to Syntax

Lecture 5 Exploring Semantics

Lecture 6 The Role of Morphology

Lecture 7 Understanding Pragmatics

Section 3: Challenges in NLP

Lecture 8 Dealing with Ambiguity

Lecture 9 Context and Nuance in NLP

Lecture 10 Figurative Language and Idioms

Section 4: Deep Dive into TensorFlow Text

Lecture 11 Why TensorFlow Text?

Lecture 12 Core Components of TensorFlow Text

Lecture 13 TensorFlow Basics

Lecture 14 TensorFlow Basics (Examples)

Section 5: Preprocessing Text Data with TensorFlow Text

Lecture 15 Tokenization Techniques

Lecture 16 Tokenization Techniques (Examples)

Lecture 17 Text Normalization

Lecture 18 Text Normalization (Examples)

Lecture 19 Stemming and Lemmatization

Lecture 20 Stemming and Lemmatization (Examples)

Section 6: Vectorization and Embeddings

Lecture 21 The Process of Vectorization

Lecture 22 The Process of Vectorization (Examples)

Lecture 23 Introduction to Word Embeddings

Lecture 24 Introduction to Word Embeddings (Examples)

Section 7: Understanding NLP Models

Lecture 0 Overview of NLP Model Architectures

Lecture 25 RNNs, LSTMs, and GRUs for NLP

Lecture 26 RNNs, LSTMs, and GRUs for NLP (Examples)

Lecture 27 CNNs and Transformers for NLP

Lecture 28 CNNs and Transformers for NLP (Examples)

Section 8: Sentiment Analysis with TensorFlow Text

Lecture 29 Introduction to Sentiment Analysis

Lecture 30 Building a Sentiment Analysis Model

Lecture 31 Building a Sentiment Analysis Model (Demo)

Lecture 32 Analyzing Model Outputs

Section 9: Text Classification with with TensorFlow Text

Lecture 33 Principles of Text Classification

Lecture 34 Building a Text Classification Model

Lecture 35 Building a Text Classification Model (Demo)

Beginners in Machine Learning and NLP: Individuals starting their journey in machine learning and natural language processing will find this course an invaluable foundation. It begins with the basics, making complex concepts accessible without prior knowledge.,Software Developers and Engineers: Programmers looking to expand their skill set into AI and NLP will discover practical applications and techniques for integrating natural language processing into software projects.,Data Scientists and Analysts: Professionals seeking to enhance their analytical capabilities will learn to leverage NLP techniques for text data, enriching their data analysis and insights.,Students in Computer Science and Related Fields: Undergraduate and graduate students will find the course a useful supplement to academic studies, providing hands-on experience and a real-world application of theoretical concepts.,Tech Enthusiasts and Hobbyists: Anyone with a curiosity about how machines understand human language and a desire to delve into AI and machine learning will find the course engaging and enlightening.,Product Managers and Entrepreneurs: Individuals in product development or entrepreneurs looking to incorporate NLP features into their products will gain a clear understanding of what's possible with current NLP technologies and how to communicate effectively with technical teams.