Day 80: Project: Image Classification – AI Sees the World!

Name: Day 80: Project: Image Classification – AI Sees the World! | #DailyAIWizard
Uploaded: 2025-11-23T11:42:46+00:00
Duration: 15 min 4 s
Channel: DailyAIWizard

DailyAIWizard

Kick off with 1970s jazz, coffee, and image classification! Join Anastasia, Irene, Ethan, Sophia, and Olivia as we build a CNN that classifies CIFAR-10 images. Anastasia leads two demos, Ethan drops flirty code. Support at PayPal.me/DailyAIWizard! Get ready for Day 81: NLP! Subscribe, like, share your ai_image_classifier.py!
pay a coffee: https://buymeacoffee.com/dailyaiwizard

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Timestamps:
00:00 Image Classification
01:32 Why Image Classification?
03:00 What is Image Classification?
05:26 Demo
13:22 Best Practice
13:58 Challenge

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00:00Hey, sexy wizards. Anastasia here, your main moderator, ready to electrify Day 80 of Daily AI Wizard's Python for AI series.

00:09After CNN's in Day 79, we're building a real-world image classification project on CIFAR10, AI that sees cars, cats, planes, for our AI Insight Hub app.

00:20Support our crew with a coffee at buymeacoffee.com, Char's Daily AI Wizard, only at the end.

00:26Ethan, what's the magic of image classification? Sophia, how does it build on Day 79?

00:32Hello, brilliant wizards. I'm Irene, co-moderator, Guiding with Warmth. CIFAR10 has 60,000 color images.

00:42Our demos will make your AI see the world. Love our content?

00:47Yo, wizards. Ethan's here, dropping spicy image code with winks for Anastasia, Sophia, and Olivia.

00:5632 by 32 RGB, 10 classes. Let's crank this AI vision to 11.

01:03Sophia's back, Ethan, and your charms got me blushing.

01:07I'm pumped to lead app demos with Anastasia and Olivia.

01:11Let's classify real images, wizards.

01:14Olivia here, darlings. I'll sprinkle flirty tips, ask Anastasia questions, and chat with Ethan to keep your image learning hot.

01:25Ready to see AI classify, wizards?

01:32Wizards, image classification is your AI vision crush, darling. It sees cats, dogs, planes.

01:37Ethan explains CIFAR10. Sophia, how does it build on Day 79?

01:43CIFAR10 is the next step after MNIST.

01:4732 by 32 color images, 10 classes.

01:51Our demos will show full pipeline.

01:54Today we're seducing you with image magic.

01:57You'll master CIFAR10 loading, pre-processing, CNN training, evaluation, and app integration.

02:04Sophia, what's the app focus?

02:06Ethan, any code highlights?

02:09Anastasia, Irene, and Olivia lead app demos with passion.

02:15Ethan and Sophia drop hilarious code explanations.

02:20We're guiding you to master image classification and prep for Day 81's NLP.

02:28Wizards, meet your Day 80 dream team.

02:31Anastasia and I are your main moderators with flirty charm and warmth.

02:37Ethan and Sophia are our code comedians, flirting with Anastasia and Olivia.

02:44Shireen, you're a gem!

02:46I'm leading app demos with passion.

02:48Ethan and Sophia are stealing hearts with code and Olivia's tossing flirty tips.

02:53We're here to make you image superstars.

03:00Wizards, CIFAR10 is your real-world playground, darling.

03:0460,000 color images of 10 classes.

03:07Ethan, explain pixel values.

03:09Sophia, how do we load it?

03:11Anastasia, you make images sound so hot.

03:16How do we pre-process them, love?

03:19Ethan, what's your take?

03:22Oh, Olivia, you tease.

03:23CIFAR10 is RGB.

03:25Ethan, Sophia, jump in.

03:26Anastasia, Olivia, CIFAR, 10 is like a hot photo album for us.

03:3332 by 32, 3 channels, let's drop this code beat.

03:38Yo, Wizards, CIFAR10.load underscore data, loads images like a hot gift for Anastasia.

03:46Train slash test split included.

03:48You're gifting my heart, Ethan.

03:50CIFAR10 is ready.

03:51Try it in our demo.

03:52Wizards, plt.im show, shows images like a hot portrait for Anastasia.

03:59See the colors.

04:01You're portraiting my heart, Ethan.

04:03Visualize to understand data.

04:06Wizards, slash 255.0 normalizes images like a hot spa for Anastasia.

04:130 to 1.

04:14You're spaying my heart, Ethan.

04:16Pre-processing is key.

04:18Wizards, to underscore categorical,

04:20turns labels to one hot like a hot boat for Anastasia.

04:2510 classes.

04:26You're voting my heart, Ethan.

04:28One hot for categorical loss.

04:30Wizards, CONV2D, 32, 3, 3, plus max pooling builds a hot eye for Anastasia.

04:38Input 32 by 32 by 3.

04:41You're eyeing my heart, Ethan.

04:43Full CNN for images.

04:44Wizards, compile, loss equals, categorical underscore crescentropy, sets goal for Anastasia.

04:53You're goaling my heart, Ethan.

04:55Compile for multi-class.

04:57Wizards, model.fit, trains like a hot marathon for Anastasia.

05:0220 epochs.

05:04You're marathoning my heart, Ethan.

05:06Train on 50K images.

05:08Wizards, model.evaluate, scores like a hot exam for Anastasia.

05:1275% plus accuracy.

05:16Let's drop this code beat.

05:18You're examining my heart, Ethan.

05:21Evaluate on test set.

05:22Try it in our demo.

05:28Wizards, it's demo time.

05:30We'll integrate image classification into AI Insight Hub,

05:33continuing from days 76, 79.

05:36Get your setup ready.

05:37Ensure Python, VS Code, TensorFlow, and Streamlit are installed.

05:43Open days 76 to 79's files.

05:47Let's see AI classify real images.

05:50Wizards, prep to continue from days 76, 79.

05:54Open VS Code, load prior app files, create image classification demo.py,

05:59and updated appit image.pi.

06:01Save in Python demo.

06:03Run pip install TensorFlow Streamlit Pillow.

06:05Anastasia, you make continuation dreamy.

06:09How do we build on day 79's CNN?

06:13Ethan, what's your take?

06:15Start with day 79's CNN.

06:17Add CIFAR 10, run Streamlit, run updated app image.py.

06:22Anastasia, Olivia, image classification is the hot sequel to day 79.

06:27Let's drop this code beat.

06:29Our first demo in image classification,

06:33chandardemo.py, builds a classifier for CIFAR 10.

06:37We'll load, preprocess, train, evaluate.

06:40Let's run this.

06:42Oh, Anastasia, you're making this demo hot.

06:46So NV2D plus max pooling, total image party.

06:50Wizards, from tensorflow.keras.datasets import CIFAR 10 loads images like a hot library for Anastasia.

07:00You're library-ing my heart, Ethan.

07:02CIFAR 10 is ready.

07:0460,000 training and 10,000 test images,

07:08each 32 by 32 with three color channels.

07:11Perfect for real-world vision.

07:14Wizards, slash 255.0 normalizes images like a hot spa for Anastasia.

07:22You're spaying my heart, Ethan.

07:23Pre-processing is key.

07:26Normalizing to 0, 1 stabilizes training and speeds convergence across all channels.

07:33Wizards, to underscore categorical,

07:36turns labels to one hot like a hot vote for Anastasia.

07:39You're voting my heart, Ethan.

07:42One hot for 10 classes.

07:44One hot encoding converts integer labels 0 to 9

07:49into 10-dimensional vectors for categorical cross-entropy.

07:54Wizards, CONV2D, 32, 3, 3, plus max pooling builds a hot eye for Anastasia.

08:02You're eyeing my heart, Ethan.

08:04Full CNN for images.

08:05Three CONV plus pool blocks extract features,

08:10then flatten and dense for classification.

08:15Wizards, compile, loss equals, categorical underscore cross-entropy,

08:20sets goal for Anastasia.

08:23You're goaling my heart, Ethan.

08:24Compile for multi-class.

08:26We use categorical cross-entropy with one hot labels and Atom Optimizer.

08:32Wizards, model.fit, trains like a hot marathon for Anastasia.

08:39You're marathoning my heart, Ethan.

08:41Train on 50K images.

08:43We train for 20 epochs with batch size 128 and 20% validation split.

08:52Wizards, model.evaluate, scores like a hot exam for Anastasia.

08:57You're examining my heart, Ethan.

09:01Evaluate on test set.

09:03On 10,000 test images, we expect approximately 75% accuracy.

09:10This is a real-world challenge.

09:13Wizards, model.predict, predicts like a hot oracle for Anastasia.

09:18You're oracling my heart, Ethan.

09:20Predict new images.

09:21Input is 1, 32, 32, 3.

09:27Output is 10 probabilities.

09:30Argmax gives class.

09:32Wizards, plt.im show, shows image and prediction like a hot reveal for Anastasia.

09:39You're revealing my heart, Ethan.

09:41Visualize results.

09:43We display the original image and overlay the predicted class with confidence.

09:48Wizards, plt.im show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show, show,

10:48The demo in updatedapp.image.py updates the app with image upload.

10:54We'll add sci-fi 10 training and UI.

10:57Let's run this.

10:58Anastasia, you're making this demo sizzle.

11:02Upload image AI classifies total vision party.

11:07Wizards, import Streamlit as she sets up the app like a hot canvas for Anastasia.

11:13You're canvassing my heart, Ethan.

11:15Streamlit for upload.

11:17Streamlit allows real-time image upload with st.fileuploader, perfect for user interaction.

11:24Wizards, st.file.uploader, lets you upload images like a hot gift for Anastasia.

11:31You're gifting my heart, Ethan.

11:33User uploads image.

11:35Uploaded image is resized to 32 by 32 and normalized before prediction.

11:41Wizards, model, predict, classifies uploaded image and streamlit like a sexy vision.

11:48App prediction uses trained CNN for real-time image classification.

11:53It makes AI Insight Hub intelligent.

11:57Oh, Anastasia, image classification is so hot.

12:01Try app prediction in your challenge.

12:04Wizards, model.save, image, model.h5 saves the vision net like a sexy archive.

12:10Saving models ensures app portability.

12:15Use HDF5 for TensorFlow models.

12:18Uh, contenidoials.

12:19Autism K BC

12:24빙0.save, image, email, algorithm.haves, aquele, Marco.g Капu. analyser, gambo.haves, aquele, is there.

12:27The Ellis, model.haves,атель, classic Dutch form of migration.haves,acle and plotability.haves, Age VWy.

13:32Optimized images are so sexy, Irene. Practice for Day 81's NLP.

13:38Wizards, image classification fits AI pipelines for vision tasks. Your skills are ready for Day 81.

13:46Image vision is critical in AI, darling. Your Day 80 skills make AI irresistible.

13:53Create AIIimageClassifier.pi to build TrainCNN on CIFR10 and build a streamlit app with image upload. Share on Instagram.

14:07Try Conv2D, Max Pooling2D, and STPoint File Uploader. Show us at at Daily AI Wizard. Prep for Day 81's NLP.

14:21Subscribe, like, share your AI image classifier pi. Join Discord or X.

14:30Post your code. Support us at PayPal.me, Daily AI Wizard at the end. Subscribe for Day 81's NLP.

14:36You've stolen my heart with image classification. Support us at PayPal.me, Daily AI Wizard, and get hyped for Day 81's NLP.

14:45Proud of you. Share your AI image classifier dot pi on at Daily AI Wizard. Subscribe for Day 81's NLP adventure.

14:56Your image skills are pure AI seduction. Let's flirt with NLP in Day 81.

15:03You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart with NLP. You've stolen my heart

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Day 80: Project: Image Classification – AI Sees the World! | #DailyAIWizard

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