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This will be a tutorial series on using AutoKeras to build an AutoML (automated machine learning) system. This first tutorial goes over what AutoML is, and how easy it is to build and train a Deep Learning Model. LINKS: installing python: https://www.python.org/ installing pip: https://pip.pypa.io/en/stable/install... **NOTE**: After rewatching the video, I felt like some things were not well explained, thus coming off as slightly confusing. Hence, I'm adding descriptions to the timesteps where I feel like further elaboration is needed. 4:38 Loading our image dataset: This is already a pre-processed dataset of images with labelled data in a NumPy array format. In the real world, if we want to do image classification, we will need to convert our .png or .jpeg images into NumPy arrays. For the sake of this first tutorial, that has not been covered yet. Hence, we will only need 1 line of code to load the dataset. Playing with real-world data is much more complicated, but I will show you in tutorial #4. 6:10 Classifiers vs regressors: These are the 2 types of models that AutoKeras supports. Classifiers allow us to predict data into groups. Ex: Predicting the age group of a person (youth vs. adult vs. elder). The possibilities are restricted to the classes we define. Regression models allow us the predict data numerically, on a scale. Ex: Predicting the exact age of a person (15.8, 47.3, 81.0, etc.) There's an infinity of possible predictions since it is a float (a fractional value) that being predicted. 9:21 You don't have to specify the number of epochs because it defaults to 1000 epochs. I specified 1 epoch because I just wanted to show that it works, you guys shouldn't do that. Same thing to max_trials, which defaults to 100. ---------- 📸 Instagram: / steven_gong_ 📱 Twitter: / stevengong_ 📝LinkedIn: / gong-steven 📂GitHub: https://github.com/Gongsta ---------- Tags Steven Gong -AutoKeras tutorial -AutoML Hashtags #AutoKeras