Kick off with 1970s jazz, coffee, and NLP! Join Anastasia, Sophia, Irene, Ethan, and Olivia as we build a sentiment classifier on IMDB reviews. Anastasia leads two demos, Ethan drops flirty code. Support at PayPal.me/DailyAIWizard! Get ready for Day 82: Sentiment Analysis! Subscribe, like, share your ai_nlp_sentiment.py!
pay a coffee: https://buymeacoffee.com/dailyaiwizard
00:00Hey, sexy wizards! Anastasia here, your main moderator, ready to electrify Day 81 of Daily AI Wizards Python for AI series.
00:10After image classification in Day 80, we're diving into Natural Language Processing, NLP, AI that reads and feels language, for our AI Insight Hub app.
00:20Support our crew with a coffee at buymeacoffee.me Daily AI Wizard, only at the end.
00:26Ethan, what's the magic of NLP? Sophia, how does it build on Day 80?
00:32Sophia's back, Ethan, and your charms got me blushing. NLP turns words into numbers. Our demos will make AI talk. Love our vibe?
00:45Hello, Brilliant Wizards. I'm Irene, co-moderator, Guiding with Warmth. NLP analyzes text, sentiment, topics, chatbots. Our demos will show real power.
00:56Yo, wizards. Ethan's here, droppin' spicy NLP code with winks for Anastasia, Sophia, and Olivia.
01:05Tokenize, vectorize, classify. Let's crank this AI brain to 11.
01:11Olivia here, darlings. I'll sprinkle flirty tips, ask Anastasia questions, and chat with Ethan to keep your NLP learning hot.
01:20Ready to make AI speak, Wizards?
01:28Wizards, NLP is your AI language crush, darling. It reads reviews, chats, translates. Ethan, explain tokenization. Sophia, how does it build on Day 80?
01:46Today, we're seducing you with NLP magic. You'll master tokenization, stop words, TF-IDF, text classification, and app integration.
01:58Sophia, what's the app focus? Ethan, any code highlights?
02:03Anastasia, Sophia, and Olivia lead app demos with passion. Ethan drops hilarious code explanations.
02:13We're guiding you to master NLP and prep for Day 82's sentiment project.
02:19Wizards, meet your Day 81 dream team. Anastasia, Sophia, and I are your main moderators with flirty charm and warmth.
02:29Ethan's our code comedian, flirting with Anastasia, Sophia, and Olivia.
02:35Oh, Irene, you're a gem. I'm leading app demos with passion, Ethan and Sophia are stealing hearts with code, and Olivia's tossing flirty tips.
02:44We're here to make you NLP superstars.
02:52Wizards, NLP is your AI language superpower, darling. It turns text into numbers.
02:57Ethan, explain tokenization. Sophia, how do we vectorize?
03:02Anastasia, you make NLP sound so hot. How do we classify sentiment, love?
03:08Ethan, what's your take?
03:10Oh, Olivia, you tease. NLP reads human language. Ethan, Sophia, jump in.
03:16Anastasia, Olivia, NLP is like a hot translator for AI.
03:21Words, right pointing arrow numbers, right pointing arrow meaning, let's drop this code beat.
03:28Yo, wizards, text, split, tokenizes like a hot word chopper for Anastasia.
03:35Words, sentences, let's drop this code beat.
03:39You're chopping my heart, Ethan.
03:41Tokenization is first step. Try it in our demo.
03:44Wizards, stop underscore words remove, the, and, like a hot filter for Anastasia.
03:52Focus on meaning.
03:53Wizards, porter stemmer, stems, running, right pointing arrow, run, like a hot root finder for Anastasia.
04:03You're rooting my heart, Ethan. Stemming normalizes words.
04:07Wizards, TFIDF vectorizer, turns words to numbers like a hot importance score for Anastasia.
04:14You're scoring my heart, Ethan. TFIDF weights words.
04:19Wizards, full NLP pipeline is like a hot factory for Anastasia.
04:24Tokenize right pointing arrow, clean right pointing arrow, vectorize right pointing arrow, classify.
04:30You're factorying my heart, Ethan. Full pipeline for sentiment.
04:34Wizards, IMDB dataset has 50k reviews like a hot movie critic for Anastasia.
04:41Positive, negative.
04:42You're reviewing my heart, Ethan. IMDB for sentiment.
04:47Wizards, IMDB load underscore data. Loads reviews like a hot script for Anastasia.
04:53You're scripting my heart, Ethan. IMDB is ready.
04:57Wizards, pad underscore sequences. Pads reviews like a hot equalizer for Anastasia.
05:03All same length.
05:05You're equalizing my heart, Ethan. Padding for RNNs.
05:08Wizards, it's demo time. We'll integrate NLP into AI Insight Hub continuing from days 77-80.
05:20Get your setup ready.
05:21Ensure Python, VS Code, TensorFlow, and Streamlit are installed.
05:27Open days 77-80's files.
05:30Let's see AI read text.
05:34Wizards, prep to continue from days 77-80.
05:40Open VS Code, load prior app files, create NLP or sentiment demo.pi, and updated app nlp.pi.
05:48Save in Python demo. Run pip install TensorFlow Streamlit.
05:55Anastasia, you make continuation dreamy. How do we build on Day80's image app?
06:01Ethan, what's your take?
06:03Start with Day80's pipeline. Add NLP. Run Streamlit. Run updated app.net nlp.pi.
06:11Anastasia, Olivia, NLP is the hot sequel to Day80.
06:16Let's drop this code beat.
06:18Our first demo in NLP or sentiment demo.py builds a sentiment classifier.
06:23We'll load IMDB, preprocess, train, evaluate. Let's run this.
06:28Oh, Anastasia, you're making this demo hot.
06:32Embedding plus LSTM, total language party.
06:36Wizards, embedding, LSTM, dense load language tools for Anastasia.
06:42You're tooling my heart, Ethan. NLP layers ready.
06:45Embedding learns word vectors.
06:48LSTM captures sequence context.
06:51Dense classifies sentiment.
06:54Oh, Ethan, you're making my LSTM skip a beat.
06:58These layers turn words into feelings. Hot, right?
07:03Wizards, IMDB load underscore data.
07:07Loads reviews like a hot script for Anastasia.
07:10You're scripting my heart, Ethan. IMDB is ready.
07:1350,000 reviews.
07:16Pre-tokenized, top 10,000 words.
07:20Perfect for NLP.
07:2250K reviews?
07:24That's like reading all the drama.
07:27And I'm here for it, Ethan.
07:28Wizards, pad underscore sequences.
07:33Maxillin equals 200 pads reviews like a hot equalizer for Anastasia.
07:39You're equalizing my heart, Ethan, padding for RNNs.
07:42All sequences must be same length for batching.
07:46200 is common.
07:49200 words?
07:50That's like cutting a movie down to the best scenes.
07:54Smart, Ethan.
07:57Wizards, embedding plus LSTM builds a hot language brain for Anastasia.
08:03You're braining my heart, Ethan.
08:04RNN for sentiment.
08:06Embedding learns word meanings.
08:08LSTM remembers context across sentences.
08:14An LSTM that remembers?
08:17Ethan, you're making me feel seen.
08:21Wizards, compile.
08:24Loss equals.
08:25Binary underscore cross entropy.
08:28Sets goal for Anastasia.
08:30You're goaling my heart, Ethan.
08:31Compile for sentiment.
08:32Binary cross entropy for positive slash negative sentiment with sigmoid output.
08:40Binary?
08:42That's like love it or hate it.
08:44No in-between.
08:45Just like my feelings for this model.
08:49Wizards, model.fit.
08:52Trains like a hot language workout for Anastasia.
08:55You're working out my heart, Ethan.
08:57Train on 25K reviews.
08:58We train for 10 epochs with batch size 128 and validation split.
09:0710 epochs?
09:08That's like 10 dates.
09:10By the end, it knows me.
09:14Wizards, model.
09:16Evaluate scores like a hot exam for Anastasia.
09:20You're examining my heart, Ethan.
09:21Evaluate on test set.
09:23Expect negative 88% accuracy.
09:27State-of-the-art for simple RNN.
09:3188%?
09:33That's like getting an A in feelings.
09:35I'm impressed.
09:38Wizards, model.
09:40Predict.
09:41Predicts sentiment like a hot critic for Anastasia.
09:44You're criticizing my heart, Ethan.
09:46Predict new reviews.
09:48Input is padded sequence.
09:50Output is probability.
09:520.5 equals positive.
09:54Over 0.5?
09:58That's a definite yes.
10:00Just like my answer to this model.
10:04Wizards, print review and prediction like a hot review for Anastasia.
10:08You're reviewing my heart, Ethan.
10:10Visualize results.
10:12We show original text and predicted sentiment with confidence.
10:17Confidence score?
10:18That's like AI saying, I'm sure this is a five-star review.
10:23I'll see you next time.
10:38Bye.
10:42Gonna be one of these.
10:45Bye.
10:45Bye.
10:47Bye.
10:47Bye.
10:48Bye.
10:49Bye.
10:50Bye.
10:51Bye.
11:51Anastasia, you're making this demo sizzle. Type a review, right pointing arrow AI feels it. Total language party. Wizards, import Streamlit as Saint sets up the app like a hot notepad for Anastasia.
12:13You're notepadding my heart, Ethan. Streamlit for text. Streamlit allows real-time text input with ST text area. Perfect for user reviews.
12:24A notepad for reviews? That's like giving AI a diary. I'm ready to spill.
12:30Wizards, street text underscore area, lets you write reviews like a hot diary for Anastasia.
12:39You're diarying my heart, Ethan, user rights review. Try it in our demo.
12:44Input text is tokenized, padded, and fed to the RNN for prediction.
12:50A diary for AI? That's like letting it read my love letters. So romantic.
12:59Wizards, model, predict. Reads review in Streamlit like a sexy critic. Buy us a coffee at the end.
13:05App Prediction uses trained RNN for real-time sentiment analysis.
13:09It makes AI Insight Hub intelligent.
13:14Oh, Anastasia. NLP is so hot. Try app prediction in your challenge.
13:20A sexy critic? That's me. AI just gave my review a five-star rating.
13:28Wizards, model.save, NLP by model.h5. Saves the language net like a sexy archive.
13:34Saving models ensures app portability. Use HDF5 for TensorFlow models.
13:43A sexy archive? That's where AI keeps all my best lines.
14:04Fading data in the background.
15:04NLP is so sexy, Irene. Practice for Day 82's Sentiment Project.
15:09Wizards. NLP fits AI pipelines for tech's tasks. Your skills are ready for Day 82.
15:20NLP is critical in AI, darling. Your Day 81 skills make AI irresistible.
15:24Create AI NLP Sentiment PY to build TrainRNN on IMDb and build a streamlit app with text input.
15:38Share on Instagram.
15:40Try embedding LSTM and ST text area.
15:45Show us at at Daily AI Wizard.
15:48Prep for Day 82's Sentiment Project.
15:51Subscribe, like, share your AI NLP Sentiment PY.
15:57Join Discord or X.
16:00Post your code. Support us at buymeacoffee.medailyaiwizard at the end.
16:05Subscribe for Day 82's Sentiment Project.
16:08You've stolen my heart with NLP.
16:09Support us at buymeacoffee.medailyaiwizard and get hyped for Day 82's Sentiment Project.
16:17Proud of you.
16:18Share your AI NLP Sentiment.py on at Daily AI Wizard.
16:24Subscribe for Day 82's Sentiment Project adventure.
16:28Your NLP skills are pure AI seduction.
16:32Let's flirt with sentiment analysis in Day 82.
Be the first to comment