Deduce the Number of Layers and Neurons for ANN
There is an optimal number of hidden layers and neurons for an artificial neural network (ANN). This tutorial discusses a simple approach for determining the optimal numbers for layers and neurons for ANN's.
Sep 2018 · 9 min read
Learn more about Deep Learning
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Recurrent Neural Networks (RNN) for Language Modeling in Python
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Introduction to Deep Learning with Keras
Learn to start developing deep learning models with Keras.
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What is Machine Learning Inference? An Introduction to Inference Approaches
Learn how machine learning inference works, how it differentiates from traditional machine learning training, and discover the approaches, benefits, challenges, and applications.
Bard vs ChatGPT for Data Science
Bard is the latest text generation LLM AI, created by Google. In this article, find out how Bard compares to the current reigning solution for Data Science, ChatGPT.
Becoming a Kaggle Grandmaster
Jean-Francois Puget is a Distinguished Engineer at NVIDIA and a 3x Kaggle Grandmaster. We talk competitive machine learning and computing on GPUs.
How the Aviation Industry Leverages Data Science
Derek Cedillo is a Senior Manager with over 25 years working in data at GE Aerospace, in the episode he shares the key components to successfully managing data science program within a large and highly regulated organization.
Docker for Data Science Cheat Sheet
In this cheat sheet, learn how to apply Docker in your Data Science projects
A Guide to Using ChatGPT For Data Science Projects
Learn how to use ChatGPT in a real-life end-to-end data science project. We will use it for project planning, data analysis, data preprocessing, model selection, hyperparameter tuning, developing a web app, and deploying it on the Spaces.