Machine learning is a field of computer science that allows for computers to accumulate data without being specifically programmed to learn. What does this mean? Computers will learn and make progress based on experiences, without programming instructions. Instead of writing codes, engineers place data into a generic algorithm. A generic algorithm makes its own logic based on the data. If you have a problem and proper data, you can use machine learning. The main goal of machine learning is to cut out human intervention in the process.
Want to learn more? Although the main concepts of machine learning are simple, you need to have proper skills to make a progress in this filed. Machine learning is related to computational statistics, mathematical optimization and data mining. Find out more about machine learning in the courses below. Our research team has prepared the list of 20 best machine learning courses for you.
Kirill Eremenko, Machine Learning A-Z™: Hands-On Python & R In Data Science: What is this course all about? Machine learning is very popular today. Becoming an expert in this field can be very challenging. In this best-seller course, you can find everything about machine learning. The teacher will talk about regression, association rule learning, deep learning and more. Through the course, you will see plenty of practical examples. These examples will help you to build your own models. Anyone who likes machine learning is a good candidate for the course. ”
Jose Portilla, Python for Data Science and Machine Learning Bootcamp: Data Scientist ranked as #1 job! According to the Glassdoor, having this job can provide you a great salary. Except for great salary, this job has other benefits. For example, you get the opportunity to work on projects which are going to solve world problems. That is enough reasons to enroll in this course. You will learn the most popular data science libraries such as NumPy, SciPy, Pandas and other. Whether you a beginner or an expert, you will learn a lot of new things here.
Frank Kane, Data Science, Deep Learning, & Machine Learning with Python: Go through 80 lectures and 12 hours of videos lessons. Frank made the technology which delivers product recommendations to the customers. He has a lot of experience in deep learning & machine learning and he wants to share it with you. The course will cover only techniques that employers are looking for. We can point out regression analysis, K-Means Clustering, Bayesian Methods and many other.
Jose Portilla, Data Science and Machine Learning Bootcamp with R: Learn more about R programming. After you go through the environment set-up, you will learn the basics of R programming. The basic part contains working with vectors and data frames. You will learn how to create amazing data visualization. The rest of the course is about machine learning. There will be lessons for beginners but also something for experienced developers.
Lazy Programmer Inc.,Bayesian Machine Learning in Python: A/B Testing: This course is all about A/B testing. People use this technique in many fields such as online advertising or marketing. This is a great experiment technique which you can use to test outcomes of two variants in a process. The teacher will talk about the traditional A/B testing. He will present the Bayesian machine learning which is a great approach to improving A/B testing. If you want to find out more about Bayesian machine learning, enroll in the course.
Lazy Programmer Inc.,Data Science: Supervised Machine Learning in Python: Can you build a machine that can think? You will find out the answer in the course. You will learn about K-Nearest Neighbor algorithm, Decision Tree, and Perceptron algorithm. Last but not least are Naive Bayes and the General Bayes Classifier. This is a very detailed course for students and professionals. The teacher suggests you take notes and ask questions during the course. The most important advice is to write your own codes instead of looking at the teacher’s code.
Lazy Programmer Inc.,Ensemble Machine Learning in Python: Random Forest, AdaBoost: Learn the Ensemble Methods! After taking this course, you will know everything about the ways of combining models. You will study Random Forest, AdaBoost algorithms, Bootstrap techniques and bias-variance trade-off. The teacher will use these algorithms in many experiments to show you how powerful they are. We have to point out that this course is not for beginners. The ideal candidates are students of machine learning, professionals, and entrepreneurs.
Loony Corn, From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase: What makes this course special? The course makes machine learning accessible to different kinds of people. It provides a very visual and practical content. You will learn the most popular techniques through interesting animations. By using these animations, the teacher wants to make this process easier for you. What will the course cover? You will learn everything about supervised & unsupervised machine learning. We can point out the concepts of classification, clustering, regression and many more. You will learn more about natural language processing with Python and sentiment analysis.
David Valentine, Introduction to Machine Learning for Data Science: People struggle with these concepts. David is an enterprise architect with over 17 years of experience. He had worked for some of the largest companies in the world. The instructor has the ability to take something that is hard and explain it in a way that makes sense. If you are a beginner with no special skills, you should enroll in the course. You are going to learn the core concepts of machine learning. What kind of a problem does machine learning solve? How to apply it to data science? Find out the answers in the course.
Rob Percival, The Complete Machine Learning Course with Python: How much money a ML engineer earns? The average salary of a Machine Learning Engineer is $166,000. If we take this into consideration, everyone should consider gaining machine learning skills. But, if you want to take the course you need to be eager to learn new things. In this course, you are going to learn how to build a powerful machine learning model. You will start the course as a beginner and end up as a real expert.
365 Careers, Machine Learning with TensorFlow + Real-Life Business Case: These are the best skills right now. According to the author, this course is better than rest because it is easy to follow. If you prefer courses with nice animations and easy content, don’t hesitate and sign up for the course. You will learn how to create algorithms, layers and backpropagation. Even if you are not familiar with these terms, you will be able to follow the course.
Lazy Programmer Inc., Cluster Analysis and Unsupervised Machine Learning in Python: Cluster analysis? Cluster analysis is a process of sorting objects in a way they will be similar to each other. The group of similar objects represents a cluster. In this course, the teacher will talk about clustering. You will learn how to get the data which you will use in supervised machine learning algorithms. Want to learn more about unsupervised machine learning? Sign up for the course.
Chandra Lingam, AWS Machine Learning, AI, SageMaker – With Python: Become an ML expert. Why should you learn machine learning? Machine learning is a must-have skill for people who work with data. This course focuses on the three aspects, algorithms, quality, and integration. If you are interested in this, enroll in the course.
Mike West, The Complete Python Course for Machine Learning Engineers: Learn Python from scratch! If you want to become a machine learning engineer, you need to learn Python first. This is a perfect opportunity for you to learn how to use Python. Python is a high-level language, which means it is easy to learn. You will learn everything you need to know to start building your own machine models in Python. Candidates who have a basic programming skills are good candidates for the course.
Mark Price, Learning for Apps: Build an app that makes predictions! You will start by learning the basics of Python. This is the most important part of the course. You are going to build a classification model from scratch to make predictions. Then you will build a neural network that classifies human writing. After finishing this course, you will have the ability of building awesome apps. If you have basic programming skills you are an adequate candidate for the course.
Jitesh Khurkhuriya, A-Z Machine Learning using Azure Machine Learning (AzureML): Develop ML models using AzureML. Learning ML can be difficult for some people. Because of that, it would be good to use some tools which will help you through this process. AzureML is a tool which will help you to build great models without writing codes. This course to learn how to use this tool.
Lazy Programmer Inc., Unsupervised Machine Learning Hidden Markov Models in Python: How to build and understand? This is the goal of the course. What are you going to learn in this course? You will learn how to measure the probability distribution of a sequence of random variables. You will realize how to use gradient descent to solve for the optimal parameters of an HMM. Since Theano and Tensorflow are the most popular libraries, you will do it in it. Students and professionals who do data analysis are ideal candidates for the course.
Eduonix-Tech., Machine Learning For Absolute Beginners: Learn core concepts of Machine Learning! It is obvious that Artificial intelligence is the future of computers. If you have ever wanted to be part of this transition, you should check this course. The teacher has prepared a great plan to teach you all about machine learning. You are going to learn all about different types of machine learning algorithms. You will put in place these algorithms in live coding projects. The teacher will cover all interesting concepts of supervised and unsupervised learning. For each part of the course, you will get exercises to be sure you understand everything. To be able to follow the course you need to have basic Python knowledge.
Lazy Programmer Inc.,Artificial Intelligence: Reinforcement Learning in Python: Learn everything artificial intelligence. According to the reviews, the lessons in the course are very well explained. What will you learn here? AI techniques that you’ve never seen before in supervised and unsupervised learning. You will understand and install 17 reinforcement learning algorithms.
Lazy Programmer Inc., Deep Learning: Recurrent Neural Networks in Python: Sequences appear everywhere. Recurrent Neural Networks have a history of being very hard to train. Recently we found the ways called vanishing gradient problem. Recurrent neural networks have become one of the most popular methods of deep learning. If you are interested in this topic, this course is for you.