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6 Best Udemy Machine Learning Courses & Tutorials of 2020

Udemy Machine Learning Courses

With so many Udemy Machine Learning courses, students find it extremely difficult to meet their needs. Learners often ask if there is a Udemy Machine Learning course for each case. The response is YES. Below are popular courses available. Registering for the right course is an important factor in your career progression. In this article, the best Udemy Machine Learning courses were selected by experts in 2020.

The main aim is to illustrate the best known courses in every category.

Select one that best suits your needs, based on your preference.

However, let’s look at the best Udemy Machine Learning courses on the market.

1. Python for Data Science and Machine Learning Bootcamp (Udemy)

Duration: Self-paced

Rating: 4.5 out of 5

This class by Udemy teaches Python in Machine Learning and Data Science programming language to help you become a wonderful data scientist. In this detailed tutorial you will learn to analyze data and use Python-powered machine learning algorithms. Jose Portilla, the trainer of this tutorial, is a professional data science trainer. He has trained the staff of many internationally renowned companies. The course is easy to start. However, if you have some programming experience, it would help.

Key Highlights:

  • Read more about natural linguistic processing, linear regression, logistic regression, neural networks, clustering K-means, spam filters, and many more.
  • Learn to use Tensorflow and Scikit-Learn, Plotly, Matplotlib, Seaborn, Pandas, NumPy, and much more.
  • Get to know Support Vector Machines, Principal Component Analysis, Recommender Systems, Deep Learning, and Neural Nets.
  • Get to know Jupyter’s Notebooks, Bias Variance, KNN Theory, Random Forest and Decision Trees and Trade-offs for Cross-Validation.
  • Get flexible lifetime access to the courses content and a certificate of completion.
  • The course offers 25 hours of on-demand HD video and code notebooks for each lecture.

You can Sign up Here

2. Machine Learning A-Z™: Hands-On Python & R In Data Science (Udemy)

Duration: Self-paced

Rating: 4.5 out of 5

Understand the use of Python and R in Data Science and Machine Learning languages in this Udemy tutorial. Learn how to build algorithms with sample code models for machine learning. Kirill Eremenko and Hadelin de Ponteves are the instructors of this course and are renowned experts in data science, artificial intelligence and machine learning. The trainees will take you to step by step through the machine learning world. Any mathematical knowledge of high school is all you need to do in this course.

Key Highlights:

  • Get to know the correct models for machine learning and the best practices to integrate them to solve any problem.
  • Learn precise forecasts, reliable machine learning models and authoritative analysis for various purposes.
  • Learn Data Preprocessing, Random Forest Recovery, Supporting Vector Recovery, Decision Tree Recovery.
  • Discover how sophisticated strategies such as strengthening, dimensional reduction, deep learning and NLP can be treated.
  • Get the entire folder, the PDF learning resources and the contents of the course regularly updated.
  • Learn Classification, KNN, Native Bytes, Eclat, Apriori, Thompson Sampling, Language Processing, Kernel PCA, Model Selection, XGBoost.

You can Sign up Here

3. Data Science and Machine Learning Bootcamp with R (Udemy)

Duration: Self-paced

Rating: 4.6 out of 5

This course by Udemy focuses exclusively on R programming, machine learning and data visualization. The course is absolutely beginners to people who do not have a programming language and wish to start their career as a data scientist. The teacher, Jose Portilla, is a specialist in data technology and has experience working in renowned organizations as head of data science. You need the required math skills to participate in this course.

Key Highlights:

  • Learn best R programming language practices for simple manipulation of data and development of data visualizations.
  • Get proper instructions for downloading and configuring R on the operating systems of Windows, Mac and Linux.
  • Read about R Matrices, R Lists, R Frames of Data, Input and Output of Data.
  • Learn how to use R for SQL, web scrapping, Excel and data processing management.
  • With this course, you can get a completion certificate and a 30-day moneyback guarantee.
  • Access the 17.5-hour video lessons, articles and other downloadable resources available on TV and mobile devices throughout their lifetimes.

You can Sign up Here

4. Machine Learning, Data Science and Deep Learning with Python (Udemy)

Duration: Self-paced

Rating: 4.5 out of 5

The other hands-on Udemy Machine Learning tutorial shows you how to use Python in machine learning. Frank Kane, a former IMDb and Amazon employee, is the mentor for this tutorial who has extensive expertise in machine learning. Frank Kane, a centre for the training of people in machine learning, computer science and big data, is the founding member of Sundog Education. In order to participate in this course, you need a machine that runs the new Python and Anaconda 3 versions.

Key Highlights:

  • Try to analyse and design A / B testing using P-values and T-tests and predict using multivariate regression and linear regression.
  • Learn best practices in the development of robust neural artificial networks using Keras and Tensorflow.
  • Learn to use user-based and object-based collaborative filtering to build an effective film advisor system.
  • Learn to identify data and images with Deep Learning and to eliminate outliers by cleaning your data input.
  • Get lifelong course access and certificate of course completion at the end of the course.
  • Learn about MatPlotLib, Seaborn, Vector Support Machines, Native Bays, Trees of Decision and many more.

You can Sign up Here

5. A-Z Machine Learning Using Azure Machine Learning (Udemy)

Duration: Self-paced

Rating: 4.5 out of 5

Learn from A to Z from the Azure Machine Learning Studio. Those who want to practice Machine Learning without coding will take this course without thought again. Learn to bring your organization great value through Learning Machine Learning on Cloud. Jitesh Khurkhuriya, the professor of the course, is an accomplished data scientist and a digital transformation consultant who has led a renowned data science and machine learning institute for 20 years. To participate in this course, you must have a free or paid subscription to Microsoft Azure and basic mathematics expertise.

Key Highlights:

  • The course provides a cheat sheet to help you select the best algorithms for machine learning and create web services for machine learning.
  • Learn how to work effectively on data science projects and create algorithms for machine learning within minutes.
  • Get to know the intuition, concepts and models of machine learning.
  • Access for 11 hours of video lessons, articles, downloading resources and a certificate of completion of the course.
  • Learn Data Processing, Classification, Text Analysis, Tuning Hyperparameters, Regression Analysis, Clustering, Feature Selection and Recommendation Framework.

You can Sign up Here

6. Machine Learning with JavaScript (Udemy)

Duration: Self-paced

Rating: 4.6 out of 5

If you want to know how to assemble Machine Learning algorithms from scratch using JavaScript, this Udemy course must be your guide. This practical Machine Learning course shows you how to use JavaScript and TensorflowJS in Machine Learning. Stephen Grider, an instructor for this course, is an engineering architect from San Francisco Bay who has worked in complex JavaScript projects for some of the leading companies. For enrolling in this course you need basic knowledge of mathematical equations, command and terminal line uses.

Key Highlights:

  • Start using the descending gradient with adjustments in the TensorFlow and the descending gradient to see how they function together.
  • Learn how machine learning works independently without relying on mysterious libraries and develop a strong intuition.
  • Using low-level TensorflowJS to overload the algorithms to construct exciting applications with JS.
  • Learn about natural binary classification, multi-value classification, image recognition, performance optimization, customized CSV loading, and how to handle JavaScript files.
  • Learn Linear Regression Class, Data Processing, Accuracy Calculation, MSE History, Optimized learning rate and Vectorized Solution.

You can Sign up Here

Wrapping Up

This is the list of the 6 Best Udemy Machine Learning Courses & Tutorials of 2020. They are popular and loved by many experienced Machine Learning learners. You will find between these courses what you need to learn in order to continue your Machine Learning journey.

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