Please recommend some best machine learning introductions

MrTree

Please recommend some best machine learning introductions [Copy link]

 

Please recommend some best machine learning introductions

microg

Here are a few ways to get started with machine learning:

1. Online Courses :

   • There are many excellent introductory machine learning courses on platforms such as Coursera and edX, such as Andrew Ng's Machine Learning course. These courses usually include video lectures, assignments, and projects to help you build your understanding of machine learning basics.

2. books :

   • Python Machine Learning: This book by Sebastian Raschka and Vahid Mirjalili introduces the basic concepts of machine learning and Python programming techniques, and provides rich examples and cases.
   • "Statistical Learning Methods": Professor Li Hang's book is a classic textbook for introductory machine learning courses, covering the basic theories and common algorithms of machine learning.

3. Online resources :

   • There are a ton of introductory tutorials and guides to machine learning on various websites and blogs, such as Towards Data Science and Analytics Vidhya.

4. Practical projects :

   • By participating in some practical projects, you can apply theoretical knowledge to real problems and deepen your understanding of machine learning. You can try some competitions on Kaggle or find some data sets to explore and model yourself.

5. Join the community :

   • Join some machine learning related communities and forums to exchange experiences and knowledge with other learners and professionals and get more learning resources and suggestions.

By combining these methods, you can gradually build up your basic knowledge and skills in machine learning and gradually move on to more complex areas and algorithms.

行者无疆1978

When it comes to getting started with machine learning, the following resources may be helpful to you:

1. "Python Machine Learning" by Sebastian Raschka and Vahid Mirjalili :

   • This book covers the basic theory and practice of machine learning, as well as how to implement various machine learning algorithms using the Python programming language. It is suitable for beginners because it covers basic concepts while providing practical programming examples.

2. Coursera's Machine Learning course :

   • This course, led by Professor Andrew Ng, is one of the most popular introductory courses for machine learning. It covers supervised learning, unsupervised learning, deep learning, and other aspects, and helps students master the basic principles and practical skills of machine learning through theoretical explanations and programming assignments.

3. Kaggle :

   • Kaggle is a well-known data science competition platform with rich data sets and competitions, as well as many high-quality tutorials and notebooks. By participating in Kaggle competitions and studying tutorials on Kaggle, you can practice machine learning algorithms and learn from other people's practical experience.

4. Machine Learning Projects and Tutorials on GitHub :

   • There are many excellent machine learning projects and tutorials on GitHub. You can learn practical experience in machine learning by reading and participating in these projects. Some well-known machine learning libraries such as scikit-learn, TensorFlow, PyTorch, etc. provide rich learning resources and sample codes.

5. Machine Learning Blogs and Forums :

   • There are many blogs and forums dedicated to discussing various aspects of machine learning, such as Medium, Towards Data Science, Stack Overflow, etc. You can learn from other people's experiences and insights by reading blog posts and participating in discussions.

The above resources are very suitable for getting started with machine learning. They cover the basic theory, practical skills and practical applications of machine learning. Choosing one or more resources to study, and constantly practicing and exploring will help you quickly master the skills of machine learning. I wish you good luck in your study!

jean_woo

When getting started with machine learning, it’s important to choose the right learning resources for you. Here are some recommended resources to get started:

1. Coursera Machine Learning Course (Andrew Ng) :

   • This course, taught by Stanford University professor Andrew Ng, is one of the classic resources for learning machine learning. The course covers the basic theory and practical applications of machine learning and provides rich programming assignments and case studies.

2. Python Machine Learning Book :

   • This book by Sebastian Raschka and Vahid Mirjalili introduces the basic concepts and common algorithms of machine learning in detail, and provides sample code implemented in Python. It is suitable for people who want to learn by doing.

3. Kaggle :

   • Kaggle is a data science competition platform that provides a large number of datasets and challenges to help you apply machine learning algorithms in practice and compete with others. Participating in Kaggle competitions is a great way to improve your machine learning skills.

4. Statistical Learning Methods (Statistical Learning Methods) Books :

   • This book by author Li Hang introduces the basic theories and common methods of statistical learning, including perceptrons, support vector machines, decision trees, ensemble learning, etc. It is a classic textbook that emphasizes both theory and practice.

5. Deep Learning Books :

   • This book by authors Ian Goodfellow, Yoshua Bengio, and Aaron Courville is an authoritative work in the field of deep learning, covering the basic concepts, theory, and practical applications of deep learning.

6. Machine Learning Micro-Specialization (Udacity) :

   • Udacity offers a series of micro-professional courses for beginners in machine learning, including basic machine learning, deep learning, and artificial intelligence. These courses usually combine theoretical explanations, programming assignments, and project practice, and are suitable for people who want to learn systematically.

7. Machine Learning Blogs and Forums :

   • Follow some blogs and forums in the field of machine learning, such as Towards Data Science, the machine learning column on Medium, and the Machine Learning sub-forum on Reddit, to learn about the latest technological advances and industry trends, and exchange experiences with other practitioners.

Choosing resources that suit your learning style and level, and continuing to practice and learn, will help you quickly master the basic knowledge and skills of machine learning.

fjdeepblue

Very good electronic information, the summary is very detailed and has reference value. Thank you for sharing