Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning.

課程信息
A working knowledge of Python and Data Analysis and Visualization techniques. A minimum of high school math.
對員工進行熱門技能培訓能否為您的公司帶來益處?
體驗 Coursera 企業版您將學到的內容有
Describe the various types of Machine Learning algorithms and when to use them
Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression
Write Python code that implements various classification techniques including K-Nearest neighbors (KNN), decision trees, and regression trees
Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation metrics
您將獲得的技能
- SciPy and scikit-learn
- Machine Learning
- regression
- classification
- Hierarchical Clustering
A working knowledge of Python and Data Analysis and Visualization techniques. A minimum of high school math.
對員工進行熱門技能培訓能否為您的公司帶來益處?
體驗 Coursera 企業版提供方
開始攻讀學士學位
授課大綱 - 您將從這門課程中學到什麼
Introduction to Machine Learning
Regression
Classification
Linear Classification
審閱
- 5 stars75.89%
- 4 stars18.68%
- 3 stars3.44%
- 2 stars0.94%
- 1 star1.03%
來自使用 PYTHON 进行机器学习的熱門評論
Very informative course, showing mostly how to use many different Machine Learning techniques. Although mathematical details are not discussed much, the intuition of the methods are discussed.
Quite an informative course, well presented material without being overbearing for newcomers to ML. Highly recommended to everyone with prior CS experience who wants to get into AI/ML workloads.
I am happy to have this online education, I drop out my nuclear engineering degree, I am happy to learn practical things with future... I work for IBM also...but I want to become a data scientis
Great course, they teach the very basic steps for data analysis world, which is awesome so we can get a solid basics understanding, the tests are in a great level (neither too easy nor too hard).
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