Getting Started with Google Colab Using PyTorch

prerequisites
intermediate Python • basics of Jupyter Notebook • basics of Google Colab • basics of PyTorch, scikit-learn, Git and GitHub • basics of Naive Bayes, neural networks, classification, and evaluation
skills learned
using Colab as a Jupyter Notebook • utilizing Colab hardware acceleration capabilities • combining Colab with PyTorch
Orsolya Putz and Zoltan Varju
1 week · 4-6 hours per week · BEGINNER
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Look inside
In this liveProject, you’ll get hands-on experience using the powerful Google Colab tool for machine learning and deep learning. Colab notebooks let you execute your data science code in Google’s cloud, getting all the benefits of Google’s incredible hardware. You’ll see how Colab works for yourself by running through simple machine learning tasks such as data preprocessing, making use of Colab’s free GPU and TPU hardware acceleration capabilities, and combining Colab with scikit-learn and PyTorch to train a classifier.

project authors

Orsolya Putz
Orsolya Putz holds a PhD in Cognitive Linguistics and devotes herself to cognitive sciences. Currently, she is an assistant lecturer at Eötvös Loránd University, Budapest, and the co-founder of Crow Intelligence, a boutique consultancy specializing in NLP and AI. Her main research areas are cognitive metaphor theory, text analytics, and cognitive background of biases in human and machine models. She also worked as a linguistic expert on various text analytics projects.
Zoltan Varju
Zoltán Varjú has been working as an expert in Natural Language Processing for 15 years. He was the head of several text analytics and enterprise search projects in the financial and health sectors. Having led Data Science and NLP teams at small companies, large corporations, and NGOs, now he is building his own enterprise, called Crow Intelligence, a boutique consultancy specialized in NLP and AI. He is the founder of the Hungarian Natural Language Processing Meetup.

prerequisites

This liveProject is for intermediate Python programmers who know the basics of data science and machine learning. To complete the second milestone of this liveProject, you will work with PyTorch. To begin this liveProject you will need to be familiar with the following:

TOOLS
  • Intermediate Python
  • Basics of Jupyter Notebook
  • Basics of Google Colab
  • Basics of PyTorch
  • Basics of scikit-learn
  • Basics of Git and GitHub
  • Basics of Google Drive
TECHNIQUES
  • Naive Bayes
  • Neural Networks
  • Classification
  • Evaluation

features

Self-paced
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Project roadmap
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Get Help
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Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.

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