10 PYTHON 🐍 libraries for machine learning.

Retweets are appreciated.
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1. NumPy (Numerical Python)

- The most powerful feature of NumPy is the n-dimensional array.

- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.

Ref: https://t.co/XY13ILXwSN
2. SciPy (Scientific Python)

- SciPy is built on NumPy.

- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.

Ref: https://t.co/ALTFqM2VUo
3. Matplotlib

- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

- You can also use Latex commands to add math to your plot.

- Matplotlib makes hard things possible.

Ref: https://t.co/zodOo2WzGx
4. Pandas

- Pandas is for structured data operations and manipulations.

- It is extensively used for data munging and preparation.

- Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage.

Ref: https://t.co/IFzikVHht4
5. Scikit Learn

- Built on NumPy, SciPy, and matplotlib, this library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction.

Ref: https://t.co/TCaQXPvKkk
6. Statsmodels

- Statsmodels for statistical modeling.

- Statsmodels is a Python module that allows users to explore data, estimate statistical models, and perform statistical tests.

Ref: https://t.co/5CXswFvpPx
7. Seaborn

- Seaborn for statistical data visualization.

- Seaborn is a library for making attractive and informative statistical graphics in Python. It is based on matplotlib.

- Seaborn aims to make visualization a central part of exploring.

Ref: https://t.co/cSxJlr09mq
8. Blaze

- Blaze for extending the capability of Numpy and Pandas to distributed and streaming datasets.

- It can be used to access data from a multitude of sources including Bcolz, MongoDB, SQLAlchemy, Apache Spark, PyTables, etc.

Ref: https://t.co/5NhpM0reaH
9. Scrapy

- Scrapy for web crawling.

- It is a very useful framework for getting specific patterns of data.

- It has the capability to start at a website home URL and then dig through web-pages within the website to gather information.

Ref: https://t.co/iEYIazAd2B
10. SymPy

- SymPy for symbolic computation.

- It has wide-ranging capabilities from basic symbolic arithmetic to calculus, algebra, discrete mathematics, and quantum physics.

- Use for formatting the result of the computations as LaTeX code.

Ref : https://t.co/hesVmRJLVj
Additional libraries, you might need:

- OS for Operating system and file operations.

- Networkx for graph-based data manipulations.

- Regular expressions for finding patterns in text data.

- BeautifulSoup for scrapping the web.

More from Machine learning

This is a Twitter series on #FoundationsOfML.

❓ Today, I want to start discussing the different types of Machine Learning flavors we can find.

This is a very high-level overview. In later threads, we'll dive deeper into each paradigm... 👇🧵

Last time we talked about how Machine Learning works.

Basically, it's about having some source of experience E for solving a given task T, that allows us to find a program P which is (hopefully) optimal w.r.t. some metric


According to the nature of that experience, we can define different formulations, or flavors, of the learning process.

A useful distinction is whether we have an explicit goal or desired output, which gives rise to the definitions of 1️⃣ Supervised and 2️⃣ Unsupervised Learning 👇

1️⃣ Supervised Learning

In this formulation, the experience E is a collection of input/output pairs, and the task T is defined as a function that produces the right output for any given input.

👉 The underlying assumption is that there is some correlation (or, in general, a computable relation) between the structure of an input and its corresponding output and that it is possible to infer that function or mapping from a sufficiently large number of examples.
With hard work and determination, anyone can learn to code.

Here’s a list of my favorites resources if you’re learning to code in 2021.

👇

1. freeCodeCamp.

I’d suggest picking one of the projects in the curriculum to tackle and then completing the lessons on syntax when you get stuck. This way you know *why* you’re learning what you’re learning, and you're building things

2.
https://t.co/7XC50GlIaa is a hidden gem. Things I love about it:

1) You can see the most upvoted solutions so you can read really good code

2) You can ask questions in the discussion section if you're stuck, and people often answer. Free

3. https://t.co/V9gcXqqLN6 and https://t.co/KbEYGL21iE

On stackoverflow you can find answers to almost every problem you encounter. On GitHub you can read so much great code. You can build so much just from using these two resources and a blank text editor.

4. https://t.co/xX2J00fSrT @eggheadio specifically for frontend dev.

Their tutorials are designed to maximize your time, so you never feel overwhelmed by a 14-hour course. Also, the amount of prep they put into making great courses is unlike any other online course I've seen.

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I hate when I learn something new (to me) & stunning about the Jeff Epstein network (h/t MoodyKnowsNada.)

Where to begin?

So our new Secretary of State Anthony Blinken's stepfather, Samuel Pisar, was "longtime lawyer and confidant of...Robert Maxwell," Ghislaine Maxwell's Dad.


"Pisar was one of the last people to speak to Maxwell, by phone, probably an hour before the chairman of Mirror Group Newspapers fell off his luxury yacht the Lady Ghislaine on 5 November, 1991."
https://t.co/DAEgchNyTP


OK, so that's just a coincidence. Moving on, Anthony Blinken "attended the prestigious Dalton School in New York City"...wait, what? https://t.co/DnE6AvHmJg

Dalton School...Dalton School...rings a

Oh that's right.

The dad of the U.S. Attorney General under both George W. Bush & Donald Trump, William Barr, was headmaster of the Dalton School.

Donald Barr was also quite a


I'm not going to even mention that Blinken's stepdad Sam Pisar's name was in Epstein's "black book."

Lots of names in that book. I mean, for example, Cuomo, Trump, Clinton, Prince Andrew, Bill Cosby, Woody Allen - all in that book, and their reputations are spotless.