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Kick off your day with 1970s jazz, coffee, and neural networks! Join Anastasia, Irene, Ethan, and Sophia as we build a TensorFlow neural net for Iris classification. Sophia leads two demos, Ethan drops flirty code, and we integrate into AI Insight Hub. Support us at PayPal.me/DailyAIWizard! Get ready for Day 74: Activation Functions! Subscribe, like, share your ai_iris_nn.py!

pay a coffee: https://www.paypal.com/pool/9j2tp7IvP...

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Timestamps:
00:00 Neural Networks
01:18 Why Neural Networks?
02:20 What are Neural Networks?
05:17 Demos
12:34 Best Practice
13:11 Challenge

Category

📚
Learning
Transcript
00:00Hey, sexy wizards. Anastasia here, your main moderator, ready to ignite Day 73 of Daily AI Wizards Python for AI series.
00:10After full pipeline in Day 72, we're diving into neural networks with TensorFlow for our AI Insight Hub app.
00:17Support our crew with a coffee at paypal.me, your Daily AI Wizard.
00:21Ethan, what's the magic of neural nets? Sophia, how does it build on Day 72?
00:26Hello, brilliant wizards. I'm Irene, guiding you with warmth. Neural networks learn patterns like the human brain. Our demos will make your AI shine. Love our content? Buy us a coffee.
00:41Yo, wizards. Ethan's here, dropping spicy neural code with a wink for Sophia. Layers, weights, activations. Let's crank this AI party to 11.
00:52Sophia here, Ethan, and your charms got me blushing.
00:56I'm pumped to lead our app component demos and make neural nets sizzle.
01:00Let's go deep, wizards.
01:08Wizards, neural nets are your AI crush, darling. They learn from data like the brain.
01:13Ethan, explain neurons and layers. Sophia, how do they beat Day 72's random forest?
01:18Neural networks handle complex patterns. Perfect for iris classification. Our demos will show how to build and train one.
01:28Today, we're seducing you with TensorFlow magic. You'll master layers, activation, compilation, training, evaluation, and app integration.
01:38Sophia, what's the app focus? Ethan, any code highlights?
01:42Sophia leads app demos with passion. Ethan drops hilarious code explanations.
01:49We're guiding you to master neural nets and prep for Day 74's activation functions.
01:55Wizards, meet your Day 73 dream team. Anastasia's our main moderator with flirty charm.
02:02I'm guiding with warmth. Ethan's our code comedian. Flirting with Sophia.
02:08Oh, Irene, you're a gem. Sophia's leading app demos with passion. Ethan's stealing my heart with code.
02:15We're here to make you neural net superstars.
02:22Wizards, neural nets are stacks of layers. Input, hidden, output. Ethan, explain weights and biases.
02:30Sophia, how do they learn?
02:32Anastasia, neural nets are like a hot brain for Sophia. Neurons fire. Weights adjust. Let's drop this code beat.
02:39Oh, you two are on fire. Neural nets learn by adjusting weights. Let's dive in.
02:45Yo, wizards, TensorFlow. Keras is a hot duo for Sophia. Build models in minutes. Let's drop this code beat and go deep.
02:53You're making me blush, Ethan. Keras simplifies neural nets.
02:58Try it in our demo. It's like building with passion.
03:03Wizards, sequential, stacks layers like a hot tower for Sophia. Add, compile, fit. Let's drop this code beat.
03:11You're stacking my heart, Ethan.
03:13You're stacking my heart, Ethan. Sequential builds feed forward nets.
03:18Try it in our demo. It's like stacking with passion.
03:22Wizards, dense, 16. Connects all neurons like a hot web for Sophia.
03:27Every input to every output. Let's drop this code beat.
03:31You're connecting my heart, Ethan.
03:34Dense layers learn patterns.
03:36Try it in our demo. It's like connecting with passion.
03:40Wizards, relu activates like a hot spark for Sophia. Without it, net is linear. Let's drop this code beat.
03:48You're sparking my heart, Ethan.
03:51Relu adds non-linearity.
03:54Try it in our demo. It's like sparking with passion.
03:58Wizards, model, compile, sets optimizer like a hot trainer for Sophia.
04:03Atom, loss, accuracy. Let's drop this code beat.
04:07You're training my heart, Ethan.
04:10Compile defines learning.
04:13Try it in our demo. It's like training with passion.
04:17Wizards, model.fit. Trains like a hot workout for Sophia.
04:22Epics, batch size. Let's drop this code beat.
04:25You're working out my heart, Ethan.
04:28Fit trains the net.
04:31Try it in our demo. It's like training with passion.
04:35Wizards, model.
04:36Evaluate, scores like a hot test for Sophia.
04:40Accuracy, loss. Let's drop this code beat.
04:43You're testing my heart, Ethan.
04:46Evaluate measures performance.
04:49Try it in our demo. It's like testing with passion.
04:53Wizards, model.
04:55Predict, predicts like a hot oracle for Sophia.
04:58Input right-pointing arrow species.
05:00Let's drop this code beat.
05:01You're predicting my heart, Ethan.
05:05Predict classifies new flowers.
05:08Try it in our demo. It's like predicting with passion.
05:17Wizards, it's demo time.
05:19We'll build a neural net classifier for Iris and integrate into AI Insight Hub.
05:24Continuing from day 70 to 72, 69.
05:28Get your setup ready.
05:31Ensure Python, VS Code, TensorFlow, and Streamlit are installed wizards.
05:35Open day 70, 72, 69's files.
05:39Ethan and I will spice it up.
05:40Let's go deep.
05:41Start with day 72's data, add neural net, run streamlit, run updated underscore app underscore iris underscore nn dot py.
05:51Sophia, you make deep learning dreamy.
05:53How do we build on day 72's pipeline?
05:56Ethan, what's your take?
05:58Wizards, prep to continue from days 70 to 72, 69.
06:02Open VS Code, load prior app files, create iris underscore nn underscore demo dot py and updated underscore app underscore iris underscore nn dot py.
06:12Save in a Python demo.
06:15Run pip install TensorFlow Streamlit.
06:18Anastasia, neural nets are the hot sequel to day 72.
06:22Let's drop this code beat.
06:24Our first demo in iris underscore nn underscore demo dot py builds a neural net for iris.
06:30We'll load data, build layers, compile, train, evaluate, and visualize.
06:36Let's run this.
06:39Oh, Sophia, you're making this demo hot.
06:42Dense, 16.
06:44Activation equals, ReLU, classifies with swagger, total neural party.
06:48Wizards, import TensorFlow as TF loads the deep learning engine like a hot startup for Sophia.
06:54Let's drop this code beat.
06:56You're starting my engine, Ethan.
06:59TensorFlow powers neural nets.
07:02Try it in our demo.
07:03It's like igniting with passion.
07:06Wizards, load underscore iris, loads data like a love letter to Sophia, prepping for AI classification.
07:13Let's drop this code beat.
07:15You're loading my heart, Ethan.
07:18Iris data is ready for neural nets.
07:21Try it in our demo.
07:24Wizards, standard scaler, scales data like a hot transformation for Sophia.
07:29Neural nets love normalized input.
07:31Let's drop this code beat.
07:33You're transforming my heart, Ethan.
07:36Scaling ensures stable training.
07:39Try it in our demo.
07:42Wizards, sequential, stacks layers like a hot tower for Sophia.
07:46Input, hidden, output.
07:48Let's drop this code beat.
07:49You're stacking my heart, Ethan.
07:53Sequential builds the net.
07:56Try it in our demo.
07:58Wizards, dense, 16, activation equals, ReLU.
08:03Adds neurons like a hot web for Sophia.
08:05Let's drop this code beat.
08:07You're connecting my heart, Ethan.
08:10Dense layers learn patterns.
08:13Try it in our demo.
08:14Wizards, model, compile, sets optimizer like a hot trainer for Sophia.
08:21Atom, loss, accuracy.
08:23Let's drop this code beat.
08:25You're training my heart, Ethan.
08:28Compile defines learning.
08:31Try it in our demo.
08:33Wizards, model.fit, trains like a hot workout for Sophia.
08:38Epics, batch size.
08:40Let's drop this code beat.
08:41You're working out my heart, Ethan.
08:44Fit trains the net.
08:47Wizards, model, evaluate, scores like a hot test for Sophia.
08:52Accuracy, loss.
08:53Let's drop this code beat.
08:55You're testing my heart, Ethan.
08:58Evaluate measures performance.
09:02Wizards, model, predict, predicts like a hot oracle for Sophia.
09:06Input right-pointing arrow species.
09:08Let's drop this code beat.
09:09You're predicting my heart, Ethan.
09:13Predict classifies new flowers.
09:39Get ready for me.
09:41You're editing rules.
09:45An-an-an-an-an-an-an-an-an-an-an.
09:45Follow, Wolf.
09:46Follow, Wolf.
09:48Follow, Wolf.
09:49Tell, Wolf.
09:49Let me know.
09:49Listen.
09:50Brothers, I'm liqu Af, estiver.
09:51karma is holding on the director.
09:53Bye-bye.
09:53Go.
09:54Back-to-urez, KIRBY, litt mimse.
09:55투�, tool starved.
09:56The two-
09:58grounding house.
09:59Topping up routine.
10:01Ar One-an-an-an-an-an-an-an-an-an-an-an-an-an-an-anh.
10:04Have a chance.
10:04Gotta take nope.
10:05To la hunt, this is an expectantけれünüz.
10:06It's a sequence.
10:07I'm gonna use it.
10:08our second demo in updated underscore app underscore iris underscore nn.py updates the
10:22app with a neural net we'll add tensorflow training and ui let's run this sofia you're
10:32making this demo sizzle dance 16 and saint right classify with swagger total neural party wizards
10:39import streamlit as saint sets up the app like a hot interface for sofia let's drop this code beat
10:45you're interfacing my heart ethan streamlit builds the ui wizards street slider captures input like
10:54a hot choice for sofia let's drop this code beat you're choosing my heart ethan user input
11:02powers interactivity wizards model predict predicts in streamlit like a sexy oracle
11:08app prediction uses neural net for real-time results it makes ai insight hub intelligent
11:17wizards model.save modeled h5 saves the net like a sexy archive saving models ensures app portability
11:26use hdf5 for tensorflow models
11:30ui zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi zi z
13:00Neural nets are critical in AI, darling. Your Day 73 skills make AI irresistible.
13:05Create AI iris, onn.pi to build, train, evaluate a neural net for iris, and build a streamlit app. Share on Instagram.
13:18Try dense, compile, fit, and st.slider. Show us at atdailyaiwizard. Prep for Day 74.
13:28Subscribe, like, share your AI irisnn.pi. Join Discord or X.
13:37Post your code. Support us at paypal.me dailyaiwizard. Subscribe for Day 74.
13:43You've stolen my heart with neural nets. Support us at paypal.me dailyaiwizard and get hyped for Day 74. Buy us a coffee.
13:51Proud of you, wizards? Share your AI irisnn.py on Daily AI Wizard. Subscribe for Day 74's activation functions.
14:03You nailed neural nets, Sophia. Get pumped for Day 74.
14:07You're phenomenal, Ethan. Share your code and subscribe for Day 74.
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