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This repo is a large sample of the coursework in the Zero to Deep Learning Bootcamp. The Bootcamp is a hands-on and immersive course to learn Machine Learning & Deep Learning fast with Python, Pandas, Matplotlib, Scikit-Learn, Keras and Tensorflow.
Participants come to accelerate and consolidate their ML and DL practical skills, as online/remote courses can only take practical skills so far. The Bootcamp provides dedicated time to learn with a teacher to achieve the next level of proficiency. This repo will help you with self-directed learning and show you what we cover in the Bootcamp, with the value of the Bootcamp coming from actually doing the labs in a supported environment.
Download Anaconda or Miniconda and then install it on your system.
git clone https://github.com/zerotodeepearning/ztdl-5-day-bootcamp.git
cd ztdl-5-day-bootcamp
We provide an environment configuration file with all the required dependencies.
conda env create
wait for the environment to create, this may take a few minutes. Note that this environment is based on Python 3.6 because Tensorflow does not support Python 3.7 yet.
conda activate ztdlbootcamp
activate ztdlbootcamp
Check that your prompt changed to
(ztdlbootcamp) $
Now you can run jupyter notebook from within the environment.
jupyter notebook
and access it from your browser at: http://localhost:8888
You are good to go! Enjoy!
Some labs require the sports images dataset, that should be located in ./data/sports/. The images can be downloaded using the download_sport.py script.
cd data/sports
python download_sport.py
Run this script a couple of times if you get any errors from aws.
If you have installed Anaconda a long time ago, you may want to update it by running:
conda update conda
and then:
conda update anaconda
conda deactivate
deactivate
If you decide to completely delete the environment from your system you should use the following command:
conda remove -y -n ztdlbootcamp --all