Please recommend some introductory tutorials on machine learning exercises

偶买噶

Please recommend some introductory tutorials on machine learning exercises [Copy link]

 

Please recommend some introductory tutorials on machine learning exercises

神经蛙1

Here are some good resources for getting started with machine learning exercises:

1. Kaggle : Kaggle is a data science competition platform that provides a large number of data sets and competitions. You can find various types of machine learning problems here and compete and learn with data scientists around the world.

2. Coursera's Machine Learning Programming Assignments : Andrew Ng's Machine Learning course provides programming assignments on the Coursera platform, which include implementing machine learning algorithms and applying them to real data sets.

yecheng

Here are some suggestions when it comes to machine learning exercises:

1. Kaggle :

   • Kaggle offers a wealth of data science and machine learning competitions, and you can find a variety of practice projects of different types and difficulty levels on Kaggle. By participating in competitions and solving practical problems, you can exercise your machine learning modeling and data analysis skills.

2. Open source projects on GitHub :

   • There are many open source machine learning projects on GitHub. You can choose some simple projects to start practicing, such as classification or regression problems based on classic data sets. Participating in these projects can make you familiar with common machine learning algorithms and tools, and learn how to apply them to practical problems.

3. Using publicly available datasets :

   • Public datasets such as the UCI Machine Learning Repository provide many standard datasets that can be used for practice. You can choose some datasets that interest you and try to apply different machine learning algorithms for data analysis and modeling.

4. Online Programming Challenge Platform :

   • Some online programming challenge platforms such as LeetCode and HackerRank also provide machine learning related exercises. The questions on these platforms cover various aspects such as machine learning basics and algorithm implementation, and are a good place to practice programming and machine learning skills.

5. Join learning communities and forums :

   • Join machine learning communities and forums to share experiences and learning resources with other learners and participate in discussions and exchanges. You can learn different practice methods and techniques from other people's experience and accelerate your own learning process.

All of the above resources are good choices for getting started with machine learning. They provide a wealth of practice opportunities and learning resources to help you improve your machine learning skills and apply them to real-world problems.

SHow111time

Of course, here are some resources for getting started with machine learning for electronics engineers:

1. Kaggle : Kaggle is a data science competition website that provides a variety of machine learning and data science practice projects. You can find various data sets and competitions on Kaggle, participate in them and compete with others, which is a good practice opportunity.

2. Machine Learning Projects on GitHub : There are many open source machine learning projects on GitHub, and you can find some simple projects to practice. You can search for some projects, such as classification, regression, clustering, etc., and choose one that you are interested in to start practicing.

3. Practice with Scikit-learn : Scikit-learn is a Python library that provides implementations of many machine learning algorithms. You can start by reading the official documentation and then try to implement tasks such as classification and regression using some simple datasets.

4. Practice with TensorFlow or PyTorch : TensorFlow and PyTorch are two popular deep learning frameworks. You can choose one of them to start learning and practicing. They both provide rich tutorials and sample codes. You can follow the official documentation and try to implement deep learning models on some classic datasets.

5. Participate in the practice projects of online courses : Many online courses, such as Coursera, Udacity, etc., will provide some practice projects for students to practice. You can choose a course that you are interested in and follow the course to complete the practice projects.

The above are several resources suitable for electronic engineers to get started with machine learning exercises. I hope they are helpful to you!

fjdeepblue

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