Day 69 Fast: Hyperparameter Tuning – Beginner’s Guide for AI Coding | #DailyAIWizard - video Dailymotion

DailyAIWizard

Kick off your coding day with a groovy 1970s jazz playlist, infused with a positive morning coffee vibe and stunning ocean views from a retro beachside room. Let the smooth saxophone and funky beats lift your spirits as you dive into Day 69 of the DailyAIWizard Python for AI series! 🚀 Join Anastasia (our main moderator), Irene, Ethan, Sophia, and Olivia as we build hyperparameter tuning for the AI Insight Hub app’s flower classifier, building on Days 65–68. Sophia leads two complex demos with Iris, Ethan drops flirty, hilarious code explanations, and Olivia adds spicy tips. Support our crew with a coffee at PayPal.me/DailyAIWizard! Perfect for beginners! 💻 Get ready for Day 70: Cross-Validation—get excited for validation magic! Subscribe, like, and share your ai_iris_tuning.py output in the comments! Connect with us on Discord, X, or Instagram (@DailyAIWizard) for more AI and jazz vibes. Code the Future, Wizards! 🌟  pay a coffee:  https://www.paypal.com/pool/9j2tp7IvP...  #PythonForAI #LearnPython #AICoding #DailyAIWizard Hashtags:  #Python #LearnPython #PythonForAI #AICoding #PythonTutorial #CodingForBeginners #ScikitLearn #Datasets #AIProgramming #TechTutorial #MachineLearning #DailyAIWizard #CodeTheFuture Tags:  Python, Learn Python, Python for AI, AI Coding, Python Tutorial, Coding for Beginners, Scikit-learn, Datasets, AI Programming, Tech Tutorial, Python 3, Coding Journey, VS Code, Beginner Programming, Machine Learning, Data Science, DailyAIWizard, Code the Future 1970s jazz, retro jazz, morning coffee, ocean views, vintage vibe, jazz playlist, positive music, coffee time, 70s music, smooth jazz, beachside jazz, funky jazz, relaxation music, morning vibes, instrumental jazz, Python, Learn Python, Python for AI, AI Coding, Python Tutorial, Coding for Beginners, TensorFlow, Neural Networks, AI Programming, Tech Tutorial, Python 3, Coding Journey, VS Code, Beginner Programming, Machine Learning, Data Science, DailyAIWizard, Code the Future

Transcript

00:00Wizards, hyperparameter tuning is your AI optimization crush, darling.

00:05It searches best parameters for models.

00:08Ethan, can you explain GridSearch CV?

00:11Sophia, how does it fit the app from day 68?

00:14Anastasia, you make tuning sound so hot.

00:18How does tuning improve models in the app, love?

00:22Ethan, what's your take on tuning in Python?

00:26Oh, Olivia, you tease.

00:27Tuning optimizes AI models.

00:30Ethan, Sophia, jump in with details.

00:33Anastasia, Olivia, tunings like a hot search, optimizing AI with flair.

00:39It's a tuning party.

00:40Let's drop this code beat for Wizards.

00:43Yo, Wizards, GridSearch CV, model, param underscore grid.

00:48Searches grids like a hot explorer for Sophia, finding AI best params.

00:53It's a grid search party.

00:54Let's drop this code beat and search some grids.

00:57You're exploring my heart, Ethan.

01:01Wizards, GridSearch CV exhaustively tunes for the app.

01:05Try it in our demo.

01:06It's like searching with passion.

01:09Wizards, randomized search CV, model, param underscore dist.

01:15Searches randomly like a hot random for Sophia, efficient AI tuning.

01:19It's a random search party.

01:21Let's drop this code beat and randomize some params.

01:24You're randomizing my heart, Ethan.

01:27Wizards, random search CV efficiently tunes for the app.

01:32Try it in our demo.

01:33It's like randomizing with passion.

01:36Wizards, param underscore grid defines search space like a hot map for Sophia, guiding AI tuning.

01:43It's a grid party.

01:44Let's drop this code beat and map some params.

01:48You're mapping my heart, Ethan.

01:50Wizards, parameter grids define tuning ranges for the app.

01:55Try it in our demo.

01:56It's like mapping with passion.

01:59Wizards, grid underscore search dot fit, x, y, fits tuned model like a hot optimizer for Sophia, finding best AI params.

02:09It's a fitting party.

02:10Let's drop this code beat and optimize some models.

02:14You're optimizing my heart, Ethan.

02:17Wizards, fitting tuned model optimizes for the app.

02:21Try it in our demo.

02:22It's like optimizing with passion.

02:24Wizards, grid underscore search.

02:28Best underscore params underscore gets best params like a hot winner for Sophia, selecting AI optimal.

02:35It's a best party.

02:36Let's drop this code beat and win some params.

02:39You're winning my heart, Ethan.

02:42Wizards, best parameters optimize the app's classifier.

02:46Try it in our demo.

02:48It's like winning with passion.

02:51Wizards, accuracy underscore score.

02:53Y underscore test, y underscore pred, evaluates tuned model like a hot score for Sophia, checking AI accuracy.

03:01It's a metrics party.

03:03Let's drop this code beat.

03:05You're scoring my heart, Ethan.

03:08Wizards, evaluating tuned model assesses app performance.

03:12Try it in our demo.

03:14It's like measuring success with passion.

03:17Wizards, SNS.

03:18Heatmap, confusion underscore matrix, visualizes confusion like a sexy matrix for Sophia, showing AI errors.

03:27It's a visualization party.

03:29Let's drop this code beat.

03:31You're matrixing my heart, Ethan.

03:34Wizards, confusion matrices show tuned errors for the app.

03:38Try it in our demo.

03:39It's like mapping success with passion.

03:43Wizards, PLT.

03:45Scatter, X underscore test, zero, X underscore test, one, C equals Y underscore pred.

03:53Visualizes predictions like a hot plot for Sophia, showing AI classes.

03:58It's a visualization party.

04:00Let's drop this code beat.

04:02You're plotting my heart, Ethan.

04:05Wizards, visualizing predictions shows app classification.

04:08Try it in our demo.

04:11It's like painting classes with passion.

04:14Wizards, scikit-learn from day 43 is a hot tool for Sophia.

04:19Grid search CV, tunes models like a sexy searcher, coding fireworks make this party epic.

04:25You're searching my heart, Ethan.

04:28Wizards, scikit-learn powers tuning for the app.

04:32Try it in our challenge.

04:33It's like optimizing AI with passion.

04:35Wizards, standard scaler, pre-processes data like a hot transformation for Sophia, scaling AI features.

04:44It's a pre-processing party.

04:46Let's drop this code beat and ready the data.

04:49You're transforming my heart, Ethan.

04:52Wizards, scikit-learn pre-processing ensures accurate tuning for the app.

04:57Try it in our demo.

04:58It's like polishing data with passion.

05:00Wizards, optimize tuning with balanced grids, CV, and scoring metrics.

05:09Use scikit-learn to ensure robust AI models for top performance in your app.

05:15Optimize tuning so sexy, Irene.

05:18Clear practices make AI optimization irresistible.

05:21Practice for day 70's cross-validation wizards and keep that code sizzling.

05:25Wizards, tuning fits AI pipelines for model optimization, improving performance.

05:33It's essential.

05:34Your skills are ready for day 70's cross-validation.

05:39Oh, Irene, tuning's critical in AI pipelines, darling.

05:42It optimizes sexily.

05:44Your day 69 skills make AI irresistible.

05:47Optimize like pros.

05:48articles.

06:06AirPeter.

06:08Air Claus.

06:08AirnenOS.

06:09Air.

06:11Air.

Day 69 Fast: Hyperparameter Tuning – Beginner’s Guide for AI Coding | #DailyAIWizard

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