Kick off with 1970s jazz, coffee, and digit classification! Join Anastasia, Irene, Ethan, and Olivia as we build a neural net that reads MNIST digits. Anastasia leads two demos, Ethan drops flirty code. Support at PayPal.me/DailyAIWizard! Get ready for Day 79: CNNs! Subscribe, like, share your ai_digit_classifier.py!
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Timestamps: 00:00 Digit Classification 01:22 Why Digit Classification? 02:36 What is Digit Classification? 05:07 Demo 12:58 Best Practice 13:30 Challenge
00:00Hey, sexy wizards! Anastasia here, your main moderator, ready to electrify Day 78 of Daily AI Wizards Python for AI series.
00:11After training in Day 77, we're building a digit classification project using MNIST, AI that reads handwriting, for our AI Insight Hub app.
00:21Support our crew with a coffee at HTTPS, ChachJachsBuyMeACoffee.com, Daily AI Wizard, but wait until the end.
00:31Ethan, what's the magic of digit classification? Olivia, how does it build on Day 77?
00:37Hello, brilliant wizards! I'm Irene, guiding with warmth.
00:42Digit classification is a classic deep learning project. Our demos will make your AI see.
00:49Love our content?
00:51Yo, wizards! Ethan's here, droppin' spicy digicode with winks for Anastasia and Olivia.
00:5828x28 pixels, 10 classes. Let's crank this AI vision to 11.
01:04Olivia here, darlings. I'll sprinkle flirty tips, ask Anastasia questions, and chat with Ethan to keep your digit learning hot.
01:13Ready to see AI read, wizards?
01:19Wizards, digit classification is your AI vision crush, darling. It reads handwritten numbers. Ethan, explain MNIST? Olivia, how does it build on Day 77?
01:32Minist is the hello world of deep learning, 60,000 training images. Our demos will show full pipeline. Support us with a coffee at the end.
01:41Today, we're seducing you with digit magic. You'll master MNIST loading, pre-processing, neural net training, evaluation, and app integration.
01:51Olivia, what's the app focus? Ethan, any code highlights?
01:55Anastasia leads app demos with passion. Ethan drops hilarious code explanations. We're guiding you to master digit classification and prep for Day 79 CNNs.
02:08Wizards, meet your Day 78 dream team. Anastasia's our main moderator with flirty charm. I'm guiding with warmth. Ethan's our code comedian. Flirting with Anastasia and Olivia.
02:21Oh, Irene, you're a gem. I'm leading app demos with passion. Ethan's stealing hearts with code. And Olivia's tossing flirty tips. We're here to make you digit superstars.
02:37Wizards, MNIST is your digit playground, darling. 70,000 images of handwritten digits. Ethan, explain pixel values. Olivia, how do we load it?
02:46Anastasia, you make digits sound so hot. How do we pre-process them, love? Ethan, what's your take?
02:56Oh, Olivia, you tease. MNIST is grayscale. Ethan, Olivia, jump in.
03:01Anastasia, Olivia, MNIST is like a hot love letter in pixels for us. 28x28, 0 to 255. Let's drop this code beat.
03:11Yo, Wizards, MNIST. Load underscore data. Loads digits like a hot gift for Anastasia. Train, test split included. Let's drop this code beat.
03:23You're gifting my heart, Ethan. MNIST is ready for training.
03:27Wizards, PLT. IM show. Shows digits like a hot portrait for Anastasia. See the handwriting.
03:34You're portraiting my heart, Ethan. Visualize to understand data.
03:39Wizards, reshape. Minus 1, 784, flattens digits like a hot pancake for Anastasia. Normalize to 0 to 1. Let's drop this code beat.
03:51You're flattening my heart, Ethan. Pre-processing is key.
03:54Wizards, to underscore categorical, turns labels to 1 hot like a hot vote for Anastasia.
04:0010 classes. You're voting my heart, Ethan. 1 hot for categorical cross-entropy.
04:07Wizards, sequential. With dense, 128, Relu, builds a hot brain for Anastasia.
04:14Input 784, output 10. You're braining my heart, Ethan. Full net for digits.
04:21Wizards, compile. Loss equals. Categorical underscore cross-entropy.
04:26Optimizer equals. Atom, sets goal and engine for Anastasia.
04:31You're goaling my heart, Ethan. Compile for multi-class.
04:35Wizards, model.fit. Trains like a hot marathon for Anastasia.
04:4010 epics, batch 12. You're marathoning my heart, Ethan. Train on 60K images.
04:47Wizards, model. Evaluate. Scores like a hot exam for Anastasia.
04:5199% plus accuracy. Let's drop this code beat.
04:56You're examining my heart, Ethan. Evaluate on test set. Try it in our demo.
05:06Wizards, it's demo time. We'll integrate digit classification into AI Insight Hub continuing from
05:12day 74-77. Get your setup ready.
05:14Ensure Python, VS Code, TensorFlow, and Streamlit are installed Wizards.
05:20Open day 74-77's files. Ethan will spice it up. Let's see AI read.
05:26Wizards, prep to continue from day 74-77.
05:30Open VS Code. Load prior app files. Create digit classification demo.py and updated app digit py.
05:38Save in Python demo. Run pip install TensorFlow Streamlit.
05:42Anastasia, you make continuation dreamy. How do we build on day 77's training?
05:50Ethan, what's your take?
05:52Start with day 77's pipeline. Add mnest. Run Streamlit. Run updated app digit.py.
05:59Anastasia, Olivia, digit classification is the hot sequel to day 77.
06:04Let's drop this code beat.
06:05Our first demo in digit classification demo.py builds a digit classifier. We'll load mnest,
06:13pre-process, train, evaluate. Let's run this.
06:17Oh, Anastasia, you're making this demo hot.
06:21Dense. 128.
06:23Reeloo, reads digits. Total vision party.
06:26Yo, Wizards, from TensorFlow.
06:29Karas.
06:30Datasets import mnest loads digits like a hot library for Anastasia.
06:34You're library-ing my heart, Ethan. Mnest is ready.
06:38Wizards, mnest load data returns 60,000 training and 10,000 test images, 28 by 28 pixels each.
06:50This is the gold standard for image classification.
06:54Wizards, reshape, minus 1, 784, and 255.0 preps digits like a hotspot for Anastasia.
07:02You're spaying my heart, Ethan. Pre-processing is key.
07:06Reshaping turns each 28 by 28 image into a 784 element vector.
07:13Normalizing to 0, 1 stabilizes training and speeds convergence.
07:19Wizards, to underscore categorical, turns labels to 1 hot like a hot vote for Anastasia.
07:251 hot encoding converts integer labels 0 to 9 into 10-dimensional vectors.
07:32This matches categorical cross-entropy loss.
07:36Wizards, dense, 128, Reeloo, builds a hot brain for Anastasia.
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