Named Entity Recognition & NER

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Unlock the Power of Calculus in Machine Learning, Deep Learning, Data Science, and AI with Python: A Comprehensive Guide to Mastering Essential Mathematical Skills"Are you striving to elevate your status as a proficient data scientist? Do you seek a distinctive edge in a competitive landscape? If you're keen on enhancing your expertise in Machine Learning and Deep Learning by proficiently applying mathematical skills, this course is tailor-made for you.Calculus for Deep Learning: Mastering Calculus for Machine Learning, Deep Learning, Data Science, Data Analysis, and AI using Python Embark on a transformative learning journey that commences with the fundamentals, guiding you through the intricacies of functions and their applications in data fitting. Gain a comprehensive understanding of the core principles underpinning Machine Learning, Deep Learning, Artificial Intelligence, and Data Science applications.Upon mastering the concepts presented in this course, you'll gain invaluable intuition that demystifies the inner workings of algorithms. Whether you're crafting self-driving cars, developing recommendation engines for platforms like Netflix, or fitting practice data to a function, the essence remains the same.Key Learning Objectives:Function Fundamentals: Initiate your learning journey by grasping the fundamental definitions of functions, establishing a solid foundation for subsequent topics.Data Fitting Techniques: Progress through the course, delving into data fitting techniques essential for Machine Learning, Deep Learning, Artificial Intelligence, and Data Science applications.Approximation Concepts: Explore important concepts related to approximation, a cornerstone for developing robust models in Machine Learning, Deep Learning, Artificial Intelligence, and Data Science.Neural Network Training: Leverage you

Learn Deep Learning from scratch. It is the extension of a Machine Learning, this course is for beginner who wants to learn the fundamental of deep learning and artificial intelligence. The course includes video explanation with introductions (basics), detailed theory and graphical explanations. Some daily life projects have been solved by using Python programming. Downloadable files of ebooks and Python codes have been attached to all the sections. The lectures are appealing, fancy and fast. They take less time to walk you through the whole content. Each and every topic has been taught extensively in depth to cover all the possible areas to understand the concept in most possible easy way. It's highly recommended for the students who don’t know the fundamental of machine learning studying at college and university level.The main goal of publishing this course is to explain the deep learning and artificial intelligence in a very simple and easy way. All the codes have been conducted through colab which is an online editor. Python remains a popular choice among numerous companies and organization. Python has a reputation as a beginner-friendly language, replacing Java as the most widely used introductory language because it handles much of the complexity for the user, allowing beginners to focus on fully grasping programming concepts rather than minute details. Below is the list of different topics covered in Deep Learning:Introduction to Deep Learning Artificial Neural Network vs Biological Neural Network Activation Functions Types of Activation functions Artificial Neural Network (ANNs) model Complex ANNs model Forward ANNs model Backward ANNs model Python project of ANNs model<strong

Dive into the transformative world of generative AI with "Mastering Deep Learning for Generative AI." This comprehensive course is designed for aspiring data scientists, tech enthusiasts, and creative professionals eager to harness the power of deep learning to create innovative generative models.What You'll Learn:Foundations of Deep Learning: Understand the core principles of neural networks, including supervised and unsupervised learning.Generative Models: Master the building and training of advanced generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers.Hands-On Projects: Engage in practical projects that guide you through creating applications in art, music, text, and design using generative AI.Model Optimization: Learn techniques to evaluate, improve, and fine-tune the performance of your generative models for real-world applications.Ethical Considerations: Explore the ethical implications and future impact of generative AI, ensuring responsible and informed application of these technologies.Course Highlights:Comprehensive Learning: From fundamentals to advanced concepts, gain a robust understanding of deep learning for generative AI.Practical Experience: Hands-on projects provide real-world experience, enhancing your ability to apply what you learn.Cutting-Edge Techniques: Stay ahead with the latest advancements in generative AI technologies.Expert Guidance: Learn from experienced instructors who provide clear explanations and valuable insights.Who Should Enroll:Aspiring Data Scientists: Those looking to specialize in deep learning a

Master the End-to-End Machine Learning Process with Python, Mathematics, and Projects — No Prior Experience Needed This course is not just another introductory tutorial. It is a complete and intensive roadmap, carefully crafted for beginners who want to become confident and capable Machine Learning practitioners. Whether you're a student, a job-seeker, or a working professional looking to transition into AI/ML, this course equips you with the core skills, hands-on experience, and deep understanding needed to thrive in today’s data-driven world.Why This Course Is Different This masterclass solves both problems by following a clear, layered, and project-oriented curriculum that blends coding, theory, and practical intuition — so you not only know what to do, but why you're doing it.You’ll go step-by-step from foundational Python to building real ML models and deploying them in real-world workflows — even touching advanced topics like ensemble models, hyperparameter tuning, regularization, and generative AI.What You’ll Learn — Inside the MasterclassFoundations of Machine Learning and Artificial Intelligence What is ML, how it differs from AI and Deep Learning.Key ML model types: Regression, Classification, Clustering.Understanding AI applications, Gen AI, and the future of intelligent systems.Knowledge checks to reinforce conceptual understanding.Python Programming from Scratch – for Absolute Beginners Starting with variables, data types, conditionals, loops, and functions.Data structures: Lists, Sets, Tuples, Dictionaries with hands-on labs.Object-oriented programming, API requests, and web scraping with Beautiful Soup.Reading and writing real-world datasets using pandas.<

This course has been designed by a specialist team of software developers who are passionate about using Java Script with Machine Learning. We will guide you through complex topics in a practical way, and reinforce learning with in-depth labs and quizzes.This is the tutorial you've been looking for to become a modern Java Script machine learning master in 2020. It doesn’t just cover the basics, by the end of the course you will have advanced machine learning knowledge you can use on you resume. From absolute zero knowledge to master - join the TensorFlow.js revolution.