In a world where artificial intelligence is becoming complex and gaining influence, creating and using a machine learning model is not only a technical endeavor but also a personal journey of exploration, challenges, and growth. Tom Pickel shared his journey of building a neural network from the ground up. Tom shared his experience in creating a neural network using Python’s basic data science packages (Numpy and Pandas) for trying to predict movements in the stock market. We mentioned loading data from stock markets, creating the Features and dataset, training networks, k-fold cross validation, choosing the best architectures, backtesting, choosing a trading strategy and more. This webinar presentation is intended for anyone who is interested in learning more about neural networks. No prior experience with neural networks is required, and perhaps it will enable participants to embark on their own journey towards developing their own machine learning models.
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