These are the tools you will need for machine learning in Python.

🧵👇

Anaconda

When you work in python, you'll be working with several frameworks and many of them work only on specific versions of python.

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Now imagine downloading a new version of python and then installing it for every framework you want to work with 😬.

Meet Anaconda which allows you to run several versions of python. It comes pre-installed with several data science and machine learning frameworks.

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Pip-env is also a way of maintaining several versions of Python and comes pre installed with Python.
You can use pip env or Anaconda, whichever works for you.

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Jupyter Notebooks

Jupyter notebooks is an IDE just like VS code or Sublime. The special thing about jupyter is that you can parts of code in mini code editors called cells. This is great for prototyping and testing code.

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Google Collab

Collab is a jupyter notebook running on google's servers which gives you access to GPUs and TPUs for training machine learning models faster for free, yes free.

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Kaggle

I like to call Kaggle the codepen for machine learning and data science.This is the place where you show off you machine learning skills. You have access to datasets for which you can make machine learning models and compete with other people around the world.

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TensorFlow

TensorFlow is a framework for machine learning,it has variants like TensorFlow.js for machine learning in the browser, TensorFlow lite for machine learning on mobile phones, and the standard TensorFlow library.

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PyTorch

PyTorch is an open-source machine learning library based on the Torch library,used for applications such as computer vision and natural language processing. It is very similar to TensorFlow in the things you can do in it with differences in the syntax.

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Matplotlib

Matplotlib is a library for plotting data into pie charts, bar charts, and whatever kinds of graphs you can imagine.

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NumPy

Numpy replaces the lists in Python with its lists, but why? Aren't the default lists good enough? The thing is that NumPy lists are much faster than Python lists, hence the wide usage of NumPy.

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SciKit Learn

SciKit learn is a machine learning library that features various classification, regression, and clustering algorithms including support vector machines. These are complex computations you may need in training your machine learning model.

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This thread took over 3 hours to make, your support by following me if you like this content will be highly appreciated! 🙏🔥

Stay tuned for more threads, good luck in your machine learning journey.

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More from Pratham Prasoon

More from Machine learning

Thanks for this incredibly helpful analysis @dgurdasani1

Two questions. 1/ Does this summarise the AZ published data :
The plan is to extend the time interval for all age groups despite it being largely untested on the over 55yrs, although the full data is not yet published


Do we have the actual numbers of over 55yr olds given a 2nd dose at c12 weeks and the accompanying efficacy data?

Not to mention the efficacy data of the full first dose over that same period?

I’d quite like to know whether I am to be a guinea pig & the ongoing risks to manage

You attached photos of excerpts from a paper. Could you attach the link?

Re Pfizer. As I understand it the most efficacious interval for dosing was investigated at the start of the trial.


Here’s the link to the

I’ve got to say that this way of making and announcing decisions is not inspiring confidence in me and I am very pro vaccination as a matter of principle, not least because my brother caught polio before vaccinations available.
10 machine learning YouTube videos.

On libraries, algorithms, and tools.

(If you want to start with machine learning, having a comprehensive set of hands-on tutorials you can always refer to is fundamental.)

🧵👇

1⃣ Notebooks are a fantastic way to code, experiment, and communicate your results.

Take a look at @CoreyMSchafer's fantastic 30-minute tutorial on Jupyter Notebooks.

https://t.co/HqE9yt8TkB


2⃣ The Pandas library is the gold-standard to manipulate structured data.

Check out @joejamesusa's "Pandas Tutorial. Intro to DataFrames."

https://t.co/aOLh0dcGF5


3⃣ Data visualization is key for anyone practicing machine learning.

Check out @blondiebytes's "Learn Matplotlib in 6 minutes" tutorial.

https://t.co/QxjsODI1HB


4⃣ Another trendy data visualization library is Seaborn.

@NewThinkTank put together "Seaborn Tutorial 2020," which I highly recommend.

https://t.co/eAU5NBucbm

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Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇

It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details):
https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha

I've read it so you needn't!

Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.

The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.

Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
Following @BAUDEGS I have experienced hateful and propagandist tweets time after time. I have been shocked that an academic community would be so reckless with their publications. So I did some research.
The question is:
Is this an official account for Bahcesehir Uni (Bau)?


Bahcesehir Uni, BAU has an official website
https://t.co/ztzX6uj34V which links to their social media, leading to their Twitter account @Bahcesehir

BAU’s official Twitter account


BAU has many departments, which all have separate accounts. Nowhere among them did I find @BAUDEGS
@BAUOrganization @ApplyBAU @adayBAU @BAUAlumniCenter @bahcesehirfbe @baufens @CyprusBau @bauiisbf @bauglobal @bahcesehirebe @BAUintBatumi @BAUiletisim @BAUSaglik @bauebf @TIPBAU

Nowhere among them was @BAUDEGS to find