株式会社PROMPT– Author –
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[AI from Scratch] Episode 229: Implementing an RNN — Building a Recurrent Neural Network
Recap and Today's Theme Hello! In the previous episode, we built a CNN (Convolutional Neural Network) to classify handwritten digits. CNNs are powerful tools for image processing as they learn features hierarchically from image data. Thi... -
[AI from Scratch] Episode 225: Implementing a Neural Network — Basic Neural Network Construction
Recap and Today's Theme Hello! In the previous episode, we discussed hyperparameter tuning to maximize model performance. By using grid search to find the best hyperparameters, we were able to significantly improve the model's accuracy. ... -
[AI from Scratch] Episode 224: Practical Hyperparameter Tuning — Using Grid Search to Find Optimal Parameters
Recap and Today's Theme Hello! In the previous episode, we discussed various methods for evaluating machine learning models, including accuracy, precision, recall, F1 score, ROC curves, and AUC scores. These metrics allow us to evaluate ... -
[AI from Scratch] Episode 226: Introduction to TensorFlow — Basics of the Deep Learning Framework
Recap and Today's Theme Hello! In the previous episode, we used Python’s Keras library to build a basic neural network for classifying handwritten digits. Keras provides a simple API, making it an excellent tool for beginners to create m... -
[AI from Scratch] Episode 223: Practical Model Evaluation — Assessing the Performance of Implemented Models
Recap and Today's Theme Hello! In the previous episode, we learned how to solve classification problems using a logistic regression model. We covered the fundamental steps, from data preprocessing to model training, prediction, and evalu... -
[AI from Scratch] Episode 221: Implementing a Simple Regression Model — Linear Regression
Recap and Today's Theme Hello! In the previous episode, we explored the basics of data preprocessing, focusing on handling missing values and feature scaling. Proper preprocessing is essential as it prepares the data to be more suitable ... -
[AI from Scratch] Episode 222: Implementing a Classification Model — Logistic Regression
Recap and Today's Theme Hello! In the previous episode, we implemented a linear regression model, one of the most fundamental models in machine learning, to predict trends based on data. Linear regression is a simple yet powerful method ... -
[AI from Scratch] Episode 250: Implementing Document Classification
Recap and Today's Theme Hello! In the previous episode, we learned about FastText, a word embedding method that uses subword information to handle unknown words and morphological variations, making it particularly useful for tasks like d... -
[AI from Scratch] Episode 249: Overview of FastText
Recap and Today's Theme Hello! In the previous episode, we covered the GloVe model, which captures the semantic relationships between words using a co-occurrence matrix. However, GloVe has limitations in dealing with out-of-vocabulary wo... -
[AI from Scratch] Episode 245: Understanding and Calculating TF-IDF
Recap and Today's Theme Hello! In the previous episode, we discussed the Bag-of-Words (BoW) model, a simple method that represents text as vectors based on word frequency. While it’s effective for many NLP tasks, the BoW model has limita... -
[AI from Scratch] Episode 246: Word Embeddings
Recap and Today's Theme Hello! In the previous episode, we discussed TF-IDF, a method for evaluating word importance based on word frequency in documents and across a corpus. While TF-IDF is effective for many applications, it does not a... -
[AI from Scratch] Episode 248: The GloVe Model
Recap and Today's Theme Hello! In the previous episode, we explored Word2Vec, a model that learns the semantic similarity of words using two methods: CBOW and Skip-gram. Word2Vec captures meaning by examining the context surrounding each... -
[AI from Scratch] Episode 247: The Mechanism of Word2Vec
Recap and Today's Theme Hello! In the previous episode, we explored Word Embeddings, where words are represented as low-dimensional vectors that capture semantic relationships, improving NLP task performance. Compared to BoW and TF-IDF, ... -
[AI from Scratch] Episode 244: The Bag-of-Words Model
Recap and Today's Theme Hello! In the previous episode, we discussed morphological analysis in Japanese. Morphological analysis is an essential process for breaking down Japanese text into words and assigning part-of-speech information, ... -
[AI from Scratch] Episode 242: Text Data Preprocessing
Recap and Today's Theme Hello! In the previous episode, we learned about the basics and applications of Natural Language Processing (NLP). NLP technology processes text and speech data for various applications, including search engines, ...
