Advanced Machine Learning Pipelines

Learn Transformers, explained: Understand the model behind GPT, BERT, and T5

State-of-the-Art Machine Learning Papers Implementation

Statistical Learning

Complete natural language processing specialization covering transformers, attention mechanisms, and modern NLP techniques.

Reinforcement Learning Specialization

This course delves into advanced machine learning techniques, including an in-depth look at ensemble learning methods like bagging, boosting, and stacking.

An in-depth exploration of machine learning applications in cybersecurity, focusing on techniques for threat detection and prevention. Participants will gain a solid grounding in machine learning fundamentals, including neural networks, clustering, and support vector machines, tailored specifically for cybersecurity contexts.

This specialization covers advanced topics in machine learning, including more complex supervised learning models and techniques.

This specialization teaches how to use machine learning for tasks like demand forecasting and predicting product usage. It covers Python libraries for data manipulation and dives into advanced AI techniques like neural networks and random forests for supply chain challenges.

This specialization covers the essential mathematical foundations for machine learning, including linear algebra, multivariate calculus, and principal component analysis (PCA). It's designed to provide the necessary mathematical background for a career in ML.

Imperial College London Mathematics for Machine Learning: Linear Algebra

This course covers advanced machine learning topics, including a detailed section on ensemble learning with decision trees, random forests, and gradient boosting.

This course delves into more advanced regression topics, including generalized linear models, mixed-effects models, and survival analysis, using the R programming language.

< Step-by-step explanation of more than 7 hours of video lessons on Supervised Machine Learning: Complete Masterclass [2023]><Instant reply to your questions asked during lessons><Weekly live talks on Supervised Machine Learning: Complete Masterclass [2023]. You can raise your questions in a live session as well><Helping materials like notes, examples, and exercises><Solution of quizzes and assignments> Welcome to the Machine Learning course!In this comprehensive course, you will learn the fundamental concepts and techniques used in Machine Learning. We will cover a range of topics from data preprocessing to model evaluation and selection, with hands-on exercises and projects to help you build and solidify your understanding of the concepts.The course is designed for beginners, but it will also be valuable for those who have some experience in programming and data analysis. You will be guided through the basics of Python programming and the most commonly used libraries for data manipulation and visualization, such as Pandas and Matplotlib.Once you have mastered the basics, we will delve into the core concepts of Machine Learning, including supervised and unsupervised learning, decision trees, random forests, clustering, neural networks, and deep learning. You will learn how to preprocess data, train and evaluate models, and optimize them for better performance.In addition to the theory, you will also have hands-on practice using real-world datasets and implementing Machine Learning algorithms with Python. By the end of the course, you will be able to apply Machine Learning techniques to solve a wide range of problems and use cases, and have the skills to further your studies in this exciting and rapidly growing field.Whether you are a student, a researcher, or a professional

Si estás buscando un curso práctico, completo y avanzado para aprender Machine Learning y Data Science con Big Data utilizando Py Spark, has venido al lugar correcto.Este curso está diseñado para aprender todo lo relacionado con el Machine Learning y Data Science en Spark como modelos de aprendizaje automático de clasificación, regresión, clustering, NLP, Pipelines y técnicas para la ingeniería de datos y preprocesamiento. También te enseñaremos a programar en Py Spark y las buenas prácticas para trabajar con Big Data, visualización de datos o analítica avanzada. Finalmente, aprenderás las últimas tecnologías que han permitido impulsar el Machine learning con Spark como ML Flow, Databricks, Spark ML o Spark Koalas.Este curso es para científicos de datos o aspirantes a científicos de datos que desean obtener capacitación práctica, con las últimas tecnologías y aplicable al mundo real en Py Spark (Python para Apache Spark)El Big Data ha revolucionado el campo del Machine Learning, permitiendo entrenar modelos sobre grandes cantidades de datos. El Machine Learning convencional con Python se ha quedado obsoleto y nuevas tecnologías como Apache Spark han cobrado gran relevancia. Este curso te enseñará todo lo que necesitas saber para posicionarte en el mercado laboral del Machine Learning y aprenderás una de las habilidades más demandadas para ingenieros de datos y científicos de datos.En este curso te enseñaremos todas las habilidades de Machine Learning con Py Spark, partiendo desde las bases hasta las funcionalidades más avanzadas. Para ello utilizaremos presentaciones visu

This is the most complete course online for learning about Python, Data Science, and Machine Learning. Join Jose Portilla's over 3 million students to learn about the future today!What is in the course?Welcome to the most complete course on learning Data Science and Machine Learning on the internet! After teaching over 2 million students I've worked for over a year to put together what I believe to be the best way to go from zero to hero for data science and machine learning in Python!This course is designed for the student who already knows some Python and is ready to dive deeper into using those Python skills for Data Science and Machine Learning. The typical starting salary for a data scientists can be over $150,000 dollars, and we've created this course to help guide students to learning a set of skills to make them extremely hirable in today's workplace environment.We'll cover everything you need to know for the full data science and machine learning tech stack required at the world's top companies. Our students have gotten jobs at Mc Kinsey, Facebook, Amazon, Google, Apple, Asana, and other top tech companies! We've structured the course using our experience teaching both online and in-person to deliver a clear and structured approach that will guide you through understanding not just how to use data science and machine learning libraries, but why we use them. This course is balanced between practical real world case studies and mathematical theory behind the machine learning algorithms.We cover advanced machine learning algorithms that most other courses don't! Including advanced regularization methods and state of the art unsupervised learning methods, such as DBSCAN.This comprehensive course is designed to be on par with Bootcamps that usually cost thousands

Do you want to master Num Py and unlock your potential in data science? This course is your comprehensive, hands-on introduction to the foundational library of modern Python computing!Num Py is the absolute core building block for essential data science and machine learning libraries like Pandas, Scikit-Learn, and PyTorch. By mastering it, you gain the technical edge needed for advanced topics like linear algebra, image processing, and fast numerical computations. If you want to start a career in Data Science or understand the engine behind Machine Learning in Python, this course is for you.What You'll Master in this Hands-On Python Course:This course will teach you everything you need to professionally use Num Py for scientific computing. We start with the basics and rapidly move into advanced techniques crucial for complex data science tasks.Foundation: Introduction to Num Py arrays, N-dimensional arrays, and the fundamental concepts of vectors and matrices.Data Analysis Tools: Leverage Universal Functions (ufuncs), Randomness, and Statistics to analyze and explore data efficiently in Python.Linear Algebra for ML: Master Basic and Advanced Linear Algebra operations, which are the backbone of all Machine Learning algorithms.Advanced Techniques: Understand Broadcasting and Advanced Indexing to write fast, memory-efficient Python code.Real-World Scientif

Welcome to the best Machine Learning and Data Science with Python course in the planet. Are you ready to start your journey to becoming a Data Scientist?In this comprehensive course, you’ll begin your journey with installation and learning the basics of Python. Once you are ready, the introduction to Machine Learning section will give you an overview of what Machine Learning is all about, covering all the nitty gritty details before landing on your very first algorithm. You'll learn a variety of supervised and unsupervised machine learning algorithms, ranging from linear regression to the famous boosting algorithms. You’ll also learn text classification using Natural Language processing where you’ll deal with an interesting problem.Data science has been recognized as one of the best jobs in the world and it’s on fire right now. Not only it has a very good earning potential, but also it facilitates the freedom to work with top companies globally. Data scientists also gets the opportunity to deal with interesting problems, while being invaluable to the organization and enjoy the satisfaction of transforming the way how businesses make decisions. Machine learning and data science is one of the fastest growing and most in demand skills globally and the demand is growing rapidly. Parallel to that, Python is the easiest and most used programming language right now and that’s the first language choice when it comes to the machine learning. So, there is no better time to learn machine learning using python than today.I designed this course keeping the beginners and those who with some programming experience in mind. You may be coming from the Finance, Marketing, Engineering, Medical or even a fresher, as long as you have the passion to learn, this course will be your first step to become a Data Scientist.I have 20 hours of best quality video contents. There are over 90 HD video lectures each rangi