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Data Professor

25 Jul, 5 tweets, 2 min read

1/ #MachineLearning Crash Course by Google
- Free course
- Learn and apply fundamental machine learning concepts
- 30+ exercises
- 25 lessons
- 15 hours to complete
- Real-world case studies
- Explainers of ML algorithms

👀🧵👇 See thread below

2/ Machine Learning Crash Course by Google
developers.google.com/machine-learni…

3/ Free machine learning crash course from Google

4/ Examples of questions answered by this course:
- How does machine learning differ from traditional programming?
- What is loss, and how do I measure it?
- How does gradient descent work?
- How do I determine whether my model is effective?

@python_engineer

5/ Perfect timing, Patrick from @python_engineer released also released a video on the Machine Learning Crash Course by Google.
Check his video out:

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More from @thedataprof

Data Professor

@thedataprof

26 Jul

1/ #Pandas is the go-to library that you need for #datawrangling for your #datascience projects when coding in #Python.
👀🧵👇 See thread below

2/ Why Do We Need Pandas?
The Pandas library has a large set of features that will allow you to perform tasks from the first intake of raw data, its cleaning and transformation to the final curated form in order to validate hypothesis testing and machine learning model building.

3/ Basics of Pandas - 1. Pandas Objects
Pandas allows us to work with tabular datasets. The basic data structures of Pandas that consists of 3 types: Series, DataFrame and DataFrameIndex. The first 2 are data structures while the latter serves as a point of reference.

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Data Professor

@thedataprof

25 Jul

1/ Interested in how Deep Learning and AI is impacting a 50-year old grand challenge in biology (protein structure folding)?
See this thread 👀🧵👇
#deeplearning #AI #biology #bioinformatics