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Data Scientist @ Alan Turing Institute | ELI5 proponent | Ph.D. Learning Analytics | Oxford & SFU Alumni

GIT FOR DATA SCIENTISTS

For scenarios like reviewing a local PR copy, bringing back a messed up file, or removing a file as part of PR.


DEEP LEARNING FOR BEGINNERS

Important recurring keywords/concepts explained in plain English

Bedroom designs generated by a StyleGAN [Made available under Creative Commons BY-NC 4.0 license]


DEEP LEARNING FOR BEGINNERS

The basic intuition behind GANs, objective functions, generator and discriminator architectures, and in-depth pseudocode walkthrough.

Image by Iván Tamás from Pixabay

Why do I need GANs?



AZURE MINI TUTORIALS

It is easier than it looks

  • Go to your kaggle account → Settings → Account → Create a new API token.
  • A kaggle.json file will be downloaded and…


MINI AZURE TUTORIALS

And how to install packages in a conda virtual environment...

conda create -y --name newenvtf
conda activate newenvtf


Deep Learning

Learn about the different layers that go into a GAN’s architecture, debug some common runtime errors, and develop in-depth intuition behind writing code in PyTorch.

Image by Comfreak from Pixabay


DEEP LEARNING FOR BEGINNERS

No need to even know what a Conv2d, Maxpool, or Batch Normalization layer does!

How quickly can you classify people into age groups based on their hands? You are one-line-of-code away from knowing. Image Source

TL;DR

ImageClassifier(max_trials = 200).fit(x = X, y = y, epochs = 3, validation_split = 0.2)

Introduction


DEEP LEARNING FOR BEGINNERS

Learn the basics of creating a neural network in PyTorch

Created by Author on Imgflip


DEEP LEARNING FOR BEGINNERS

Explaining an end-to-end binary image classification model with MaxPool2D, Conv2D, and Dense layers.

Image by Pete Linforth from Pixabay

Varshita Sher

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