Published 7/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.26 GB | Duration: 8h 16m
Get hands-on experience with real-world machine learning projects and master the latest machine learning techniques.
What you’ll learn
Understand the basics of machine learning, artificial intelligence, and deep learning.
Be able to build and train machine learning models.
Be able to build and train machine learning models.
Be able to use Python for machine learning.
Be able to deploy machine learning models to production.
Be able to use TensorFlow, a popular deep learning library in Python.
Be able to use scikit-learn, a popular machine learning library in Python.
Requirements
A willingness to learn: Machine learning is a complex topic, so learners should be willing to put in the effort to learn the material.
Some experience with programming: This could be in any programming language, but Python is the most popular choice for machine learning.
Description
Machine learning is one of the most in-demand skills in the tech industry today. Machine learning engineers are responsible for building and deploying machine learning models that solve real-world problems. In this course, you will learn the skills you need to become a machine learning engineer.We will start by covering the basics of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. We will then discuss the different types of machine learning models, such as neural networks, decision trees, and support vector machines. We will also cover the latest machine learning techniques and frameworks, such as TensorFlow and PyTorch.In addition to the theoretical concepts, we will also provide you with hands-on experience with real-world machine learning projects. You will build a machine learning model to classify images, predict customer churn, and recommend products.By the end of this course, you will have the skills you need to build, deploy, and maintain machine learning models. You will also be prepared for a career in machine learning engineering.This course is designed for anyone who wants to learn machine learning engineering. No prior experience with machine learning is required.The course is delivered in a video format, with each lecture accompanied by slides and code examples. You will also have access to a forum where you can ask questions and interact with other learners.If you are interested in learning machine learning engineering, then this course is for you. Enroll today and start your journey to becoming a machine learning engineer!Here are some of the benefits of taking this course:Learn the skills you need to build and deploy machine learning modelsMaster the latest machine learning techniques and frameworksGet hands-on experience with real-world machine learning projectsPrepare for a career in machine learning engineeringJoin a growing community of machine learning enthusiasts
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Fundamentals of Machine Learning
Lecture 2 Machine Learning Vs Artificial Intelligence Vs Neural Networks
Lecture 3 Working with Data for Machine Learning
Lecture 4 The Types of Machine Learning
Section 3: TensorFlow
Lecture 5 Introduction to TensorFlow | Part One
Lecture 6 Exploring TensorFlow
Section 4: Core Learning Algorithms
Lecture 7 Machine Learning algorithms
Section 5: Neural Networks
Lecture 8 Understanding Neural Networks
Section 6: Computer Vision – Convolutional Neural Networks
Lecture 9 Understanding CNNs & Computer Vision
Section 7: Natural Language Processing with Recurrent Neural Networks (RNNs)
Lecture 10 the Power of Recurrent Neural Networks (RNNs) for NLP
Section 8: Reinforcement Learning with Q-Learning: Mastering Intelligent Decision-Making
Lecture 11 A Framework for Optimal Decision-Making
Section 9: Conclusion and Next Steps
Lecture 12 Building your own ML journey
Beginners: If you’re new to machine learning, this course is a great place to start. I will teach you everything you need to know to get started, from the basics of mathematics and programming to the latest trends in machine learning.,Intermediate learners: If you have some experience with machine learning, this course will help you take your skills to the next level. I will cover more advanced topics, such as deep learning and neural networks.,Professionals: If you’re a professional who wants to stay up-to-date on the latest trends in machine learning, this course is for you. I will cover the latest research and development in the field, so you can be sure that you’re using the latest techniques.
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