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Beginner. No background in the topic needed.
166K views4 years ago1 recommendation
AI and machine learningNeural networks and deep learningTraining and serving models
Jeremy Howard explains how neural networks work by building a basic model and implementing a neural net in Excel.
Introduction and survey "Lesson 0" How to fast.ai How to do a fastai lesson How to not self-study Highest voted student work Pets breeds detector Paperspace JupyterLab Make a better pet detector Comparison of all (image) models Try out new models Get the categories of a model What’s in the model What does model architecture look like Parameters of a model Create a general quadratic function Fit a function by good hands and eyes Loss functions Automate the search of parameters for better loss The mathematical functions ReLu: Rectified linear function Infinitely complex function A chart of all image models compared Do I have enough data? Interpret gradients in unit? Learning rate Matrix multiplication Build a regression model in spreadsheet Build a neuralnet by adding two regression models Matrix multiplication makes training faster Watch out! it’s chapter 4 Create dummy variables of 3 classes Taste NLP fastai NLP library vs Hugging Face library Homework to prepare you for the next lesson Many thanks to bencoman, wyquek, Raymond Wu, and fmussari on forums.fast.ai for writing the transcript. Timestamps thanks to "Daniel 深度碎片" on forums.fast.ai.What people say. Recommended for its intuitive demonstration of a neural network built inside Microsoft Excel.
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