Here is a great set of cheat sheet on some of the following topics:
- Supervised learning
- Unsupervised learning
- Deep learning
- Probability and statistics
- Linear algebra
- Tips and tricks including performance metrics
https://stanford.edu/~shervine/teaching/cs-229/
Hope you liked the cheat sheets on different topics of machine learning and data science.
I have been recently working in the area of Data Science and Machine Learning / Deep Learning. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc. You may follow me on Linkedin.
Latest posts by Ajitesh Kumar (see all)
- Correlation & Correlation Heatmap using Seaborn - September 29, 2020
- Beta Distribution Explained with Python Examples - September 24, 2020
- Bernoulli Distribution Explained with PythonExamples - September 23, 2020
