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A large part of our product is training and using a machine learning model. As such, we chose one of the best coding languages, Python, for machine learning. This coding language has many packages which help build and integrate ML models. For the main portion of the machine learning, we chose PyTorch as it is one of the highest quality ML packages for Python. PyTorch allows for extreme creativity with your models while not being too complex. Also, we chose to include scikit-learn as it contains many useful functions and models which can be quickly deployed. Scikit-learn is perfect for testing models, but it does not have as much flexibility as PyTorch. We also include NumPy and Pandas as these are wonderful Python packages for data manipulation. Also for testing models and depicting data, we have chosen to use Matplotlib and seaborn, a package which creates very good looking plots. Matplotlib is the standard for displaying data in Python and ML. Whereas, seaborn is a package built on top of Matplotlib which creates very visually pleasing plots.
Pros of H2O
- Highly customizable2
- Very fast and powerful2
- Auto ML is amazing2
- Super easy to use2
Pros of PredictionIO
- Predict Future8
Pros of scikit-learn
- Scientific computing26
- Easy19
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Cons of H2O
- Not very popular1
Cons of PredictionIO
Cons of scikit-learn
- Limited2
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What is H2O?
What is PredictionIO?
What is scikit-learn?
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