Ajit jaokar's Blog – October 2019 Archive (1)
Understanding the applications of Probability in Machine Learning
This post is part of my forthcoming book The Mathematical Foundations of Data Science. Probability is one of the foundations of machine learning (along with linear algebra and optimization). In this post, we discuss the areas where probability theory could apply in machine learning applications. If you want to know more about…
ContinueAdded by ajit jaokar on October 27, 2019 at 10:30am — No Comments
Latest Blog Posts
- Feature engine python package for feature engineering
- Why do some traditional engineers not trust Data Science?
- Why we need more Bayesian trained data scientists than frequentist post COVID 19 ..
- How to approach the study of algorithms?
- 23 sources of data bias for #machinelearning and #deeplearning
- IoT Anomaly detection - algorithms, techniques and open source implementation
- Free book – for #datascience interviews - Guide to competitive programming
Most Popular Blog Posts
- Correlation does not equal causation but How exactly do you determine causation?
- Free book on Statistics: Larry Wasserman’s All of Statistics
- A free self-paced learning path for #machinelearning and #deeplearning
- Feature engine python package for feature engineering
- A simplified explanation for Understanding the Mathematics of Deep Learning
- Rule of thumb: Which AI / ML algorithms to apply to business problems
- A methodology for solving problems with DataScience for Internet of Things - Part Two
Resources
Videos
© 2020 Data Science Central ®
Powered by
Badges | Report an Issue | Privacy Policy | Terms of Service
