NLP & Text Processing

This course teaches how to use Py Spark for streaming data processing and Natural Language Processing (NLP) applications. It is aimed at data professionals who want to build scalable data-streaming applications and perform advanced NLP tasks on large datasets.

Notice: Effective Dec 24, 2024, this course has been thoroughly updated. Rest assured, it will consistently be refreshed to ensure its ongoing relevance and effectiveness.Unlock the Future of AI: Master Generative AI & NLP with Python Embark on a Revolutionary Journey into the World of AI: Become a Master of Generative AI & Natural Language Processing (NLP)Are you ready to unlock the full potential of Artificial Intelligence? This comprehensive, two-part course is designed to take you on an in-depth, hands-on journey through the cutting-edge fields of Generative AI and Natural Language Processing (NLP). Whether you're a beginner looking to enter the world of AI, a professional seeking to upgrade your skills, or an innovator aiming to stay ahead of the curve, this course offers everything you need to master these transformative technologies and prepare for the future.Course Overview:Our Generative AI & NLP with Python course will empower you to dive deep into the heart of AI technologies. Through expert-led instruction and hands-on practice, you will acquire the skills necessary to develop, implement, and leverage AI tools and techniques in real-world applications. This course goes beyond theoretical knowledge, focusing on practical, real-world projects to ensure that you not only learn but also apply what you’ve learned.Part 1: Generative AI Unleashed - Transforming Ideas into Reality In the first part of this course, we will explore the exciting world of Generative AI and Large Language Models (LL Ms). You’ll discover how these technologies are revolutionizing industries across the globe by generating creative, data-driven solutions to complex problems.Introduction to Generative AI: Learn the essential principles, history, and evolution of Gener

Do not take this course if you are an ML beginner. This course is designed for those who are interested in pure coding and want to fine-tune LL Ms instead of focusing on prompt engineering. Otherwise, you may find it difficult to understand.Welcome to "Mastering Transformer Models and LLM Fine Tuning", a comprehensive and practical course designed for all levels, from beginners to advanced practitioners in Natural Language Processing (NLP). This course delves deep into the world of Transformer models, fine-tuning techniques, and knowledge distillation, with a special focus on popular BERT variants like Phi2, LLAMA, T5, BERT, DistilBERT, MobileBERT, and TinyBERT.Course Overview:Section 1: Introduction Get an overview of the course and understand the learning outcomes.Introduction to the resources and code files you will need throughout the course.Section 2: Understanding Transformers with Hugging Face Learn the fundamentals of Hugging Face Transformers.Explore Hugging Face pipelines, checkpoints, models, and datasets.Gain insights into Hugging Face Spaces and Auto-Classes for seamless model management.Section 3: Core Concepts of Transformers and LL Ms Delve into the architectures and key concepts behind Transformers.Understand the applications of Transformers in various NLP tasks.Introduction to transfer learning with Transformers.Section 4: BERT Architecture Deep Dive Detailed exploration of BERT's architecture and its importance in context understanding.Learn about Masked Language Modeling (MLM) and Next Sentence Prediction (NSP) in BERT.Understand BERT fine-tuning and evaluation techniques.Section 5: Practical Fine-Tuning with BERT</strong

Träumst du davon...die Möglichkeiten von KI-Tools wie ChatGPT, Claude, Gemini und Neuroflash voll auszuschöpfen, um produktiver und kreativer zu arbeiten?mit präzisen Prompts die besten Ergebnisse aus generativer KI herauszuholen und deinen Workflow zu optimieren?Prompts zu erstellen, die für verschiedene Anwendungen wie Content-Erstellung, Produktivität, Marketing oder Automatisierung maßgeschneidert sind?deine Fähigkeiten im Umgang mit Large Language Models (LLM) zu erweitern, um innovative Lösungen für persönliche und berufliche Herausforderungen zu entwickeln?Dann ist dieser Kurs „Prompt Engineering für KI: ChatGPT, Claude, Gemini und LLM“ genau das Richtige für dich! Von der Einführung in die grundlegenden Funktionen bis hin zu fortgeschrittenen Strategien zeigt dir dieser Kurs, wie du die volle Leistung moderner KI-Tools nutzen kannst. Lerne, wie du mit gezielten Prompts Ergebnisse erzielst, deine Arbeitsprozesse vereinfachst und sogar neue kreative Ansätze entwickelst. Entdecke, wie generative KI nicht nur deine Projekte voranbringt, sondern auch eine neue Dimension von Effizienz und Innovation eröffnet.Was du lernen wirst:Einführung in ChatGPT, Gemini und Claude: Du erhältst eine Einführung in die führenden KI-Tools ChatGPT, Google Gemini und Claude. Der Kurs zeigt dir, wie du einen kostenlosen Account erstellst, dich mit den Benutzeroberflächen vertraut machst und erste Prompts eingibst. Außerdem erfährst du, wie du mit jedem Tool gezielt arbeiten kannst, unabhängig von deiner bisherigen Erfahrung.Erste Prompts bei LLM's eingeben: Lerne, wie du effektive Prompts formulierst, die dir präzise und hilfreiche Ergebnisse liefern. Du erfährst, wie du B

More and more evidence has demonstrated that graph representation learning especially graph neural networks (GN Ns) has tremendously facilitated computational tasks on graphs including both node-focused and graph-focused tasks. The revolutionary advances brought by GN Ns have also immensely contributed to the depth and breadth of the adoption of graph representation learning in real-world applications. For the classical application domains of graph representation learning such as recommender systems and social network analysis, GN Ns result in state-of-the-art performance and bring them into new frontiers. Meanwhile, new application domains of GN Ns have been continuously emerging such as combinational optimization, physics, and healthcare. These wide applications of GN Ns enable diverse contributions and perspectives from disparate disciplines and make this research field truly interdisciplinary.In this course, I will start by talking about basic graph data representation and concepts like node data, edge types, adjacency matrix and Laplacian matrix etc. Next, we will talk about broad kinds of graph learning tasks and discuss basic operations needed in a GNN: filtering and pooling. Further, we will discuss details of different types of graph filtering (i.e., neighborhood aggregation) methods. These include graph convolutional networks, graph attention networks, confidence GC Ns, Syntactic GC Ns and the general message passing neural network framework. Next, we will talk about three main types of graph pooling methods: Topology based pooling, Global pooling and Hierarchical pooling. Within each of these three types of graph pooling methods, we will discuss popular methods. For example, in topology pooling we will talk about Normalized Cut and Graclus mainly. In Global pooling, we will talk about Set2Set and Sort Pool. In Hierarchical pooling, we will talk about diff Pool, g Pool and SAG Pool. Next, we will talk about three unsupervised graph neural network architectures: Graph

Are you ready to explore the limitless possibilities of Artificial Intelligence? In this course, Complete Artificial Intelligence: From Basics to Generative AI, we’ve designed a comprehensive journey to help you master the exciting world of AI and Machine Learning. Whether you're a beginner curious about AI or someone looking to enhance your skills, this course provides a clear and structured pathway for success.We start by covering the fundamentals of Artificial Intelligence, breaking down the concepts into simple, easy-to-follow lessons. You'll learn the basics of Machine Learning, including Supervised and Reinforcement Learning, and how these approaches are applied to solve real-world problems. As you progress, we move to Deep Learning, focusing on building Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs) to tackle complex tasks like image and speech recognition.But that’s not all—we also take a deep dive into the rapidly growing field of Generative AI. From understanding how Generative Adversarial Networks (GANs) work to exploring cutting-edge technologies like Transformers and Large Language Models (LL Ms), you’ll gain insights into how AI creates everything from realistic images to human-like text. Plus, we cover Natural Language Processing (NLP), explaining how AI understands and generates human language.Whether you're here to start a new career, enhance your knowledge, or simply explore AI, this course is your gateway to the future of technology. Enroll now and take the first step toward mastering the art and science of AI!

Learn the theory of Seq2Seq in only 2 hours! A straight to the point course for those of you who don't have a lot of time.Embark on an academic adventure with our specialized online course, meticulously designed to illuminate the theoretical aspects of Seq2Seq (Sequence to Sequence) models within the realms of Deep Learning and Natural Language Processing (NLP).What This Course Offers:Exclusive Focus on Seq2Seq Model Theories: Our course curriculum is devoted to exploring the intricacies and theoretical foundations of Seq2Seq models. Delve into the principles and mechanics that make these models a cornerstone in NLP and Deep Learning.In-Depth Conceptual Insights: We take you through a comprehensive journey, dissecting the core concepts, architectures, and training of Seq2Seq models. Our focus is on fostering a deep understanding of these complex theories.Theory-Centric Approach: Emphasizing theoretical knowledge, this course intentionally steers away from practical coding exercises. Instead, we concentrate on building a robust conceptual framework around Seq2Seq models.Ideal for Theoretical Enthusiasts: This course is perfectly suited for students, educators, researchers, and anyone with a keen interest in the theoretical aspects of Deep Learning and NLP, specifically in the context of Seq2Seq models.Join us to master the theoretical nuances of Seq2Seq models in Deep Learning and NLP. Enroll now for an enlightening journey into the heart of these transformative technologies!And last but not least you will get a great series of Prizes providing extra case studies in Artificial Intelligence made by ChatGPT.Can't wait to see you inside the class,Kirill &amp;&nbsp;Hadelin

Caution before taking this course:This course does not make you expert in R programming rather it will teach you concepts which will be more than enough to be used in machine learning and natural language processing models.About the course:In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.This course covers following topics:1. R programming concepts:&nbsp;variables, data structures:&nbsp;vector, matrix, list, data frames/ loops/ functions/ dplyr package/ apply() functions2. Web scraping:&nbsp;How to scrape titles, link and store to the data structures3. NLP technologies:&nbsp;Bag of Word model, Term Frequency model, Inverse Document Frequency model4. Sentimental Analysis:&nbsp;Bing and NRC lexicon5. Text mining By the end of the course you’ll be in a journey to become Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.

Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE.After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a cipher decryption algorithm. These have applications in warfare and espionage. We will learn how to build and apply several useful NLP tools in this section, namely, character-level language models (using the Markov principle), and genetic algorithms.The second project, where we begin to use more traditional "machine learning", is to build a spam detector. You likely get very little spam these days, compared to say, the early 2000s, because of systems like these.Next we'll build a model for sentiment analysis in Python. This is something that allows us to assign a score to a block of text that tells us how positive or negative it is. People have used sentiment analysis on Twitter to predict the stock market.We'll go over some practical tools and techniques like the NLTK (natural language toolkit) library and latent semantic analysis or LSA.Finally, we end the course by building an article spinner. This is a very hard problem and even the most popular products out there these days don't get it right. These lectures are designed to just get you started and to giv

Deep Learning is a hot topic today! This is because of the impact it's having in several industries. One of the fields in which deep learning has the most influence today is Natural Language Processing.To understand why Deep Learning based Natural Language Processing is so popular; it suffices to take a look at the different domains where giving a computer the power to understand and make sense out of text and generate text has changed our lives.Some applications of Natural Language Processing are in:Helping people around the world learn about any topic ChatGPT Helping developers code more efficiently with Github Copilot.Automatic topic recommendation in our Twitter feeds Automatic Neural Machine Translation with&nbsp; Google TranslateE-commerce search engines like those of Amazon Correction of Grammar with Grammarly The demand for Natural Language Processing engineers is skyrocketing and experts in this field are highly paid, because of their value. However, getting started in this field isn’t easy. There’s so much information out there, much of which is outdated and many times don't take the beginners into consideration :(In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step and project-based approach. You shall be using TensorFlow 2 (the world's most popular library for deep learning, built by Google) and Hugging Face transformers (most popular NLP focused&nbsp;library ). We shall start by understanding how to build very simple models (like Linear regression model for car price prediction and RNNs text classifiers for movie revi

Unlock the Future with AI: Master ChatGPT, ChatGPT o4 &amp; the LLM Revolution!(Freshly Updated May 2025! This course is continuously revised to keep you at the cutting edge.)Are you ready to command the most transformative technology of our era? Welcome to "Exploring the Technologies Behind ChatGPT, ChatGPT o4 &amp; LL Ms" – your definitive launchpad to mastering the groundbreaking power of Large Language Models. This isn't just another AI course; it's an immersive journey designed to catapult you from curious novice to confident expert in the electrifying world of Natural Language Processing (NLP). Whether you're taking your first steps into AI or seeking to sharpen your advanced skills, prepare to be transformed.Why Is This Your Unmissable Opportunity?In today's hyper-digital landscape, understanding LL Ms isn't just an advantage—it's a necessity. These revolutionary technologies are the engines driving innovation across every conceivable industry. They're reshaping how we interact, automating complex tasks, creating compelling content, and unlocking efficiencies previously unimaginable.This course is meticulously crafted for:Aspiring Developers: Build next-gen AI applications.Data Scientists: Supercharge your analytical capabilities.Researchers: Push the boundaries of NLP.AI Enthusiasts: Deepen your passion with practical skills.Business Professionals: Leverage AI to drive strategic growth.We provide the critical tools, profound insights, and hands-on experience you need to not just understand, but harness these powerful technologies. Join the vanguard of the AI revolution and become an architect of the future!What Awaits You Inside? Prepare to Achieve Mastery:</p

Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, Gemini Pro, Llama 3, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.Hello friends!Welcome to Data Science: Transformers for Natural Language Processing.Ever since Transformers arrived on the scene, deep learning hasn't been the same.Machine learning is able to generate text essentially indistinguishable from that created by humans We've reached new state-of-the-art performance in many NLP&nbsp;tasks, such as machine translation, question-answering, entailment, named entity recognition, and more We've created multi-modal (text and image) models that can generate amazing art using only a text prompt We've solved a longstanding problem in molecular biology known as "protein structure prediction"In this course, you will learn very practical skills for applying transformers, and if you want, detailed theory behind how transformers and attention work.This is different from most other resources, which only cover the former.The course is split into 3 major parts:Using Transformers Fine-Tuning Transformers Transformers In-DepthPART&nbsp;1: Using Transformers In this section, you will learn how to use transformers which were trained for you. This costs millions of dollars to do, so it's not something you want to try by yourself!We'll see how these prebuilt models can already be used for a wide array of tasks, including:text classification (e.g. spam detection, sentiment analysis, document categorization)named entity recognitiontext summarizationmachine transla

Who Is This Course For?Are you curious about Artificial Intelligence but overwhelmed by buzzwords like NLP, Machine Learning, Deep Learning, and Generative AI? Do you want to understand AI without getting lost in technical jargon? If so, this course is perfect for you! No prior experience required! Whether you're a complete beginner, a student exploring AI for the first time, a professional looking to future-proof your career, or simply someone fascinated by how AI is shaping the world—you’ll walk away with clear, practical knowledge that puts you ahead of the curve.Why This Course?AI is no longer the future—it’s the present! Companies worldwide are integrating AI into their businesses, and those who understand it have a massive advantage in any industry. This course will give you a strong foundation in AI concepts without requiring coding or advanced mathematics. You’ll not only understand what AI is but also how it works and where it's headed, making you confident in conversations, career choices, and future learning.&nbsp; &nbsp;What makes this course special?Clarity over complexity – AI explained in simple, beginner-friendly terms.Practical relevance – Understand AI's real-world applications and how it's shaping industries.Guided learning roadmap – Follow Andrew Ng’s structured approach to mastering AI after this course.Don’t miss out on the AI revolution! Start learning today and gain the knowledge that will set you apart in the world of tomorrow. Enroll now!

Embark on a comprehensive journey into the world of artificial intelligence with "Learn AI - The Ultimate A-Z Guide." This course is designed to empower you with the skills and knowledge to apply AI in various aspects of life, whether you're a beginner or have prior experience. Each section offers detailed insights and practical applications tailored to enhance your proficiency and creativity with AI.Section 1: AI for Birthdays &amp; Presents Discover innovative ways to use AI for creating personalized birthday experiences and gifts. Learn to harness ChatGPT for unique gift ideas tailored to individual preferences, and delve into generating custom images using AI tools. Explore the practical side of bringing digital creations to life through Printify and understand the process of converting text descriptions into 3D models. This section also covers the intricacies of 3D printing, guiding you through each step to produce tangible models from your AI-generated designs. Additionally, learn about 3D scanning technologies, utilizing AI to capture and enhance real-world objects digitally.Section 2: AI for Health &amp; Fitness Transform your health and fitness journey with AI-driven solutions that cater to your personal needs. This section explores using AI to craft tailored workout and meal plans, ensuring they align with your fitness goals and dietary preferences. Discover how AI can enhance your gym experience, from optimizing equipment usage to analyzing your form. Learn to create and import workout playlists using AI, making your fitness routine more engaging. Explore the applications of AI in grocery shopping, helping you make healthier choices, and delve into the realm of mental health with AI.Section 3: ChatGPT Features Unlock the full potential of ChatGPT by mastering its diverse features. This section provides an in-depth exploration of custom GP Ts, teaching you how to tailor them for s

Sevgili arkadaşlar merhaba,NLP’nin temel kavramlarını ve modern dil modellerinin gelişimini keşfetmeye hazır mısınız? Bu kursta, NLP’nin başlangıcından Büyük Dil Modelleri’nin (LL Ms) yükselişine kadar olan süreci adım adım ele alacağız.Kurs, temel bilgilerden karmaşık modellere doğru bir öğrenme deneyimi sunacak şekilde tasarlandı. Amacımız, NLP’nin gelişimini sade ve anlaşılır bir şekilde aktararak, teorik altyapıyı en iyi şekilde kavramanızı sağlamak. NLP’nin evrimindeki her adımı sırasıyla inceleyecek ve bu alandaki kavramları derinlemesine öğreneceksiniz. Eğer bu alanda yeniyseniz veya mevcut bilginizi derinleştirmek istiyorsanız, bu kurs sizin için ideal!Eğitimin içerisinde Doğal Dil İşlemenin evrim basamaklarını aşağıdaki sıra ile öğreneceğiz:KURAL TABANLI NLP (RULE-BASED NLP)İSTATİSTİKSEL NLP (STATISTICAL NLP)FREKANS TABANLI METİN VEKTÖRİZASYONU (FREQUENCY-BASED TEXT VECTORIZATION)BAĞLAMDAN BAĞIMSIZ STATİK TEMSİLLER (CONTEXT-INDEPENDENT STATIC EMBEDDINGS)BAĞLAMLAŞTIRILMIŞ TEMSİLLER (CONTEXTUALIZED EMBEDDINGS)BU KURS SİZE NE KAZANDIRACAK?NLP'nin temel kavramlarından LLM'lere uzanan yolculuğu anlama fırsatı.Büyük Dil Modellerinin (LL Ms) temel mantığı, mimarisi ve uygulama alanları hakkında detaylı bilgi.NLP projelerinde kullanabileceğiniz pratik ve teorik bilgi.Güncel NLP araçları ve modelleriyle çalışma becerisi.Kurs; Makine Öğrenimi, Derin Öğrenme, Doğal Dil İşleme ve Büyük Dil Modelleri (LL Ms) alanlarında uzmanlaşan Musa Bayır tarafından hazırlanmıştır. Eğer NLP ve Büyük Dil Modelleri (LL Ms) hakkında kapsamlı teorik bilgi edinmek ve bu alandaki bilginizi derinleştirmek istiyorsanız hemen kayıt olun.

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided. Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. This course is a down-to-earth, shy but confident take on machine learning techniques that you can put to work today Let’s parse that. The course is down-to-earth : it makes everything as simple as possible - but not simpler The course is shy but confident : It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff. You can put ML to work today : If Machine Learning is a car, this car will have you driving today. It won't tell you what the carburetor is. The course is very visual : most of the techniques are explained with the help of animations to help you understand better. This course is practical as well : There are hundreds of lines of source code with comments that can be used directly to implement natural language processing and machine learning for text summarization, text classification in Python. The course is also quirky. The examples are irreverent. Lots of little touches: repetition, zooming out so we remember the big picture, active learning with plenty of quizzes. There’s also a peppy soundtrack, and art - all shown by studies to improve cognition and recall. What's Covered: Machine Learning: Supervised/Unsu