https://github.com/nuitrcs/NUIT_tensorflow
General information about RCS Python Workshops can be found in the Python Workshops Repository. This includes information about software installations and general Python resources.
In order to ensure a seamless workshop experience, we will not depend on local Jupyter/Python installations, but instead work from Google Colab. Consequently, there's no need to install nor download anything - you will work from notebooks directly in Google Colab.
Instructions for opening a notebook:
- Log in to Google
- Open Google Colab: https://colab.research.google.com
- Go to File > Open notebook
- Click on the GitHub tab
- Search for my username ('allemanau'), and once found, select this repository ('NUIT_tensorflow')
- Open the current notebook
We will go through the steps together at the end of the short intro presentation.
Learn enough to be dangerous about deep learning, and practice implementing basic models with TensorFlow 2.0.
- Learn about fundamental deep learning principles and challenges
- Practice implementing and evaluating models with TensorFlow and Keras
- Work with convolutional layers, pooling layers, and data augmentation
General machine learning, data science, and deep learning resources:
Data Science Central - A great online group of data science enthusiasts where you can find everything related to machine learning, predictive modeling, data science and more.
KDnuggets - A great source of news anything ML and Data Science.
Towards Data Science - Place to share concepts, ideas and code
Coursera, edx, udacity, Kadenze courses. I would strongly recommend Andrew Ng's machine learning courses.
General TensorFlow resources and more specific tutorials that cover multiple topics can be found on Tensorflow Website.