tl;dr A step-by-step tutorial to automatically generate subtitles from a video using audio segmentation and Wav2Vec2. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough. Continue on if you prefer reading the code here....
tl;dr A step-by-step tutorial to generate spoken singlish audio from text automatically using a pipeline of a Malaya Speech model and applying speech enhancement. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
tl;dr A step-by-step tutorial to train a hate speech detection model to classify text containing hate speech. The trained model has a BERT-based transformer architecture. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
A recent paper by Japanese researchers shows how they built a system to fully automate the process of translating manga from Japanese to English. Given a manga page, the system translates and replaces the original Japanese text with English and formats it nicely on the page. Contextual Information from Manga Images One of the novel innovations of this recent paper titled “Towards Fully Automated Manga Translation” by Japanese researchers Ryota Hinami et al....
tl;dr A step-by-step tutorial to train a BioBERT model for named entity recognition (NER), extracting diseases and chemical on the BioCreative V CDR task corpus. Our model is #3-ranked and within 0.6 percentage points of the state-of-the-art. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
tl;dr A step-by-step tutorial to train a state-of-the-art model with BERT for named entity recognition (NER) in mandarin, 中文命名实体识别. Our model beats the state-of-the-art by 0.7 percentage points. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
tl;dr A step-by-step tutorial to train a state-of-the-art model with flair and BERT for named entity recognition (NER) in mandarin, 中文命名实体识别, on a Weibo dataset. Our model beats the state-of-the-art by 20+ percentage points. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
tl;dr A step-by-step tutorial to train a state-of-the-art model for sentiment analysis on mandarin food delivery reviews using the XLNet architecture. We will use Google Colab’s free Jupyter Notebook in the cloud. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
tl;dr A step-by-step tutorial to train a state-of-the-art model for named entity recognition (NER), the task of identifying persons, organizations and locations from a piece of text. Practical Machine Learning - Learn Step-by-Step to Train a Model A great way to learn is by going step-by-step through the process of training and evaluating the model. Hit the Open in Colab button below to launch a Jupyter Notebook in the cloud with a step-by-step walkthrough....
tl;dr A step-by-step tutorial to train a sentiment analysis model to classify polarity of IMDB movie reviews with XLNet using a free Jupyter Notebook in the cloud. The IMDB Movie Reviews Dataset and XLNet The Internet Movie Database (IMDb) movie reviews dataset is a very well-established benchmark (since 2011) for sentiment analysis performance. It’s probably the first large-ish (50,000 train+test), balanced sentiment analysis dataset, making it a very nice dataset for benchmarking on....