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Learn to build image embeddings using pre-deep learning models in less than an hour with James Briggs. Ideal for object detection and image classification.
Learn to build an Open-domain Q&A reader model in Python with James Briggs. This less than 1-hour material covers ODQA components, data preprocessing, and fine-tuning.
Explore data augmentation in NLP with James Briggs' concise guide. Learn to generate or label data automatically, focusing on the 'in-domain' flavor of AugSBERT. Less than 1hr workload.
Learn to build an API using Flask in Python with James Briggs. Understand request types, endpoints, and data manipulation in under an hour.
Learn to build an input pipeline for a transformer model using raw OSCAR training data in under an hour with James Briggs.
Learn vector similarity search techniques in AI with James Briggs. Understand TF-IDF, BM25, and Sentence-BERT in less than an hour.
Learn traditional methods for similarity search in AI, including Jaccard Similarity, w-shingling, and Levenshtein distance, in under an hour with James Briggs.
Learn to pre-train BERT models using Next Sentence Prediction (NSP) with James Briggs in under an hour. Ideal for enhancing language understanding in specific use cases.
Learn to build and deploy your own Python packages to the Python Package Index (PyPI) with James Briggs in under an hour.
Learn to apply transformers for sentiment analysis on long texts in Python, overcoming the token limit, in under an hour with James Briggs.
Learn to build custom Q&A transformer models using Python in this 1-2 hour material by James Briggs. Gain a data science superpower with HuggingFace transformers and PyTorch.
Join James Briggs for a 1-2 hour code-along session to build a GME stock chart using Python, PlotLy, and the AlphaVantage API.
Master Regular Expressions and their application in Python in under an hour with James Briggs' tutorial, covering metacharacters, quantifiers, capture groups, and more.
Learn to build a transformer model for sentiment analysis using HuggingFace's Transformers library in TensorFlow 2 with Python, in under an hour with James Briggs.
Learn to construct efficient input pipelines for Machine Learning in TF2, offered by James Briggs, in less than an hour.
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