@ryu46nokke: 強豪校バスケ部大学選びのリアルな悩み⑤ #遠藤龍之介 #バスケ #バスケ部 #TikTokSportsキャンペーン #TikTok秋のスポーツキャンペーン

スパイダー遠藤龍之介マン

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Region: JP

Tuesday 29 September 2026 11:00:00 GMT

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Comments

aaa :

バスケってスポ推決まるのこんなギリギリなん？

2026-09-30 04:26:34

123

たかとんかち :

ガチで続き見たい

2026-09-29 11:06:16

586

tamachan647 :

焦らすねぇ…笑気になって30分しか寝れない

2026-09-29 11:23:31

393

サッカーすき :

東洋大学いっとるやん

2026-09-29 13:36:36

5

カス :

東洋も日大も大差ないけどな

2026-09-29 12:29:41

98

お昼ご飯はおやつ :

続き出たら叫んで

2026-09-29 12:30:29

9

ゆどーふ。 :

続き見たい！って思ってプロフ飛んだらネタバレ見ちまった、、、

2026-09-29 11:19:58

43

ねこ :

続きでたら冷笑して

2026-09-30 00:19:15

3

ゆ :

続き出たら教えてください

2026-09-29 15:28:15

5

vivi :

日大の方がバスケ強いと思ってた

2026-09-30 02:20:38

7

大翔 :

続き出たら教えてくれませんか

2026-09-29 21:59:55

1

re_07 :

続き早くみたぁーい！

2026-09-29 11:16:01

5

ねぇ、ししゃも？！ :

Nの方がいいと思うんだけどTの方が今は人気なの？

2026-09-29 18:48:59

1

おっふ :

監督無責任すぎない？笑

2026-09-30 08:44:20

5

M :

次出たら教えてーーーー

2026-09-29 17:15:34

1

sotyan 🚹（12） :

続き出たら叫んで

2026-09-29 22:07:12

7

こむぎ :

気になるー！続きでたら誰か返信してー

2026-09-29 13:01:14

0

D.しんじ :

ちょい長いな

2026-09-30 10:27:17

2

みこ🐟 :

続きでたら踊ってください

2026-09-30 01:31:04

0

🤩 :

続き出たら叫んで

2026-09-29 22:43:18

1

かつぽん :

無理ですって連絡やろなぁ

2026-09-30 06:34:07

1

どん :

今日池袋いましたか！？

2026-09-29 14:44:25

1

ユリ :

やっぱ結末伸ばすねー

2026-09-29 14:14:53

1

ちゅん :

大学の夏休みは9月いっぱいのとこもあるから、それで返事まだって可能性もあるわなw

2026-09-30 03:26:59

1

🐯木浪光司🦁🎩（キナチカ） :

お願い！！いい結果になってくれ！

2026-09-29 13:28:18

2

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NLP has evolved from simple text rules to systems that can understand, generate, and reason over language. Here’s the landscape you should know. 👇 1️⃣ TEXT PROCESSING 📝 The foundation of NLP. 🔤 Tokenization 🧹 Text Cleaning 🏷️ Part-of-Speech Tagging 🌳 Stemming & Lemmatization 🔎 Named Entity Recognition 2️⃣ CLASSICAL NLP 📊 Before modern deep learning, NLP relied heavily on statistical and feature-based methods. 📌 Bag of Words 📌 TF-IDF 📌 N-grams 📌 Naive Bayes 📌 Logistic Regression 📌 SVM 3️⃣ WORD REPRESENTATIONS 🔢 Convert language into numerical representations. 🔹 Word2Vec 🔹 GloVe 🔹 FastText 🔹 Embeddings The goal: Words → Vectors → Mathematical representations 4️⃣ SEQUENCE MODELS 🔄 Neural networks designed to process sequences. 🧠 RNN ⚡ LSTM 🔁 GRU Used for: 📝 Text generation 🌍 Translation 🎙️ Speech 📊 Sequence prediction 5️⃣ TRANSFORMERS ⚡ Transformers changed modern NLP. The key idea: Attention They allow models to understand relationships between tokens across a sequence. 6️⃣ PRE-TRAINED LANGUAGE MODELS 🧠 Instead of training a model from scratch for every task, models can first learn general language patterns from large datasets. Examples: 🔹 BERT 🔹 RoBERTa 🔹 T5 🔹 GPT 7️⃣ LARGE LANGUAGE MODELS 🤖 Modern LLMs can perform many language tasks through a single general-purpose model. Applications include: 💬 Chatbots 📝 Summarization 🌍 Translation 💻 Code Generation 🔎 Information Extraction 🧠 Reasoning 8️⃣ EMBEDDINGS & SEMANTIC SEARCH 🔎 Modern NLP isn’t only about generating text. Embeddings represent meaning in vector space. Used for: 🔍 Semantic Search 📚 Document Retrieval 🎯 Recommendation 🧩 Similarity Search 9️⃣ RAG 📚 Retrieval-Augmented Generation Combines: 🔎 Retrieval ➕ 📚 External Knowledge ➕ 🤖 LLM Generation Useful for building AI applications grounded in specific documents and knowledge bases. 🔟 NLP → MODERN AI AGENTS 🤖 Language models can now interact with tools and external systems. 🧠 Reason 🔎 Retrieve 🛠️ Use tools 🔄 Execute multi-step workflows 🎯 Complete tasks 🗺️ THE NLP EVOLUTION Text Processing ⬇️ Classical NLP ⬇️ Word Embeddings ⬇️ RNN / LSTM / GRU ⬇️ Transformers ⬇️ Pre-trained Models ⬇️ LLMs ⬇️ RAG ⬇️ 🤖 AI Agents ⸻ 💡 WHAT TO LEARN If you’re starting NLP: Python → Text Processing → Statistics → Classical NLP → Embeddings → Deep Learning → Transformers → LLMs → RAG → AI Agents Don’t skip the fundamentals just because LLMs are popular. Understanding the layers underneath modern AI makes the new stuff much easier to understand. 🚀 #NLP #NaturalLanguageProcessing #AI #creatorsearchinsights #programming

NLP has evolved from simple text rules to systems that can understand, generate, and reason over language. Here’s the landscape you should know. 👇 1️⃣ TEXT PROCESSING 📝 The foundation of NLP. 🔤 Tokenization 🧹 Text Cleaning 🏷️ Part-of-Speech Tagging 🌳 Stemming & Lemmatization 🔎 Named Entity Recognition 2️⃣ CLASSICAL NLP 📊 Before modern deep learning, NLP relied heavily on statistical and feature-based methods. 📌 Bag of Words 📌 TF-IDF 📌 N-grams 📌 Naive Bayes 📌 Logistic Regression 📌 SVM 3️⃣ WORD REPRESENTATIONS 🔢 Convert language into numerical representations. 🔹 Word2Vec 🔹 GloVe 🔹 FastText 🔹 Embeddings The goal: Words → Vectors → Mathematical representations 4️⃣ SEQUENCE MODELS 🔄 Neural networks designed to process sequences. 🧠 RNN ⚡ LSTM 🔁 GRU Used for: 📝 Text generation 🌍 Translation 🎙️ Speech 📊 Sequence prediction 5️⃣ TRANSFORMERS ⚡ Transformers changed modern NLP. The key idea: Attention They allow models to understand relationships between tokens across a sequence. 6️⃣ PRE-TRAINED LANGUAGE MODELS 🧠 Instead of training a model from scratch for every task, models can first learn general language patterns from large datasets. Examples: 🔹 BERT 🔹 RoBERTa 🔹 T5 🔹 GPT 7️⃣ LARGE LANGUAGE MODELS 🤖 Modern LLMs can perform many language tasks through a single general-purpose model. Applications include: 💬 Chatbots 📝 Summarization 🌍 Translation 💻 Code Generation 🔎 Information Extraction 🧠 Reasoning 8️⃣ EMBEDDINGS & SEMANTIC SEARCH 🔎 Modern NLP isn’t only about generating text. Embeddings represent meaning in vector space. Used for: 🔍 Semantic Search 📚 Document Retrieval 🎯 Recommendation 🧩 Similarity Search 9️⃣ RAG 📚 Retrieval-Augmented Generation Combines: 🔎 Retrieval ➕ 📚 External Knowledge ➕ 🤖 LLM Generation Useful for building AI applications grounded in specific documents and knowledge bases. 🔟 NLP → MODERN AI AGENTS 🤖 Language models can now interact with tools and external systems. 🧠 Reason 🔎 Retrieve 🛠️ Use tools 🔄 Execute multi-step workflows 🎯 Complete tasks 🗺️ THE NLP EVOLUTION Text Processing ⬇️ Classical NLP ⬇️ Word Embeddings ⬇️ RNN / LSTM / GRU ⬇️ Transformers ⬇️ Pre-trained Models ⬇️ LLMs ⬇️ RAG ⬇️ 🤖 AI Agents ⸻ 💡 WHAT TO LEARN If you’re starting NLP: Python → Text Processing → Statistics → Classical NLP → Embeddings → Deep Learning → Transformers → LLMs → RAG → AI Agents Don’t skip the fundamentals just because LLMs are popular. Understanding the layers underneath modern AI makes the new stuff much easier to understand. 🚀 #NLP #NaturalLanguageProcessing #AI #creatorsearchinsights #programming

: e hoàng say anh huy lắm rùi đấy nháaa 😡 #keonhyeon

: e hoàng say anh huy lắm rùi đấy nháaa 😡 #keonhyeon

Bạn thích kiểu mùi nào 🤔 #nuochoanam #nuochoa #apaniche

Bạn thích kiểu mùi nào 🤔 #nuochoanam #nuochoa #apaniche

#explore #fyp #foryou #fypシ

#explore #fyp #foryou #fypシ

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