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The Training: Mastering SentenceTransformers for Semantic Analysis and Similarity Search in NLP training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training: Mastering SentenceTransformers for Semantic Analysis and Similarity Search in NLP training, Learni provides the following teaching resources:
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Presentation of embedding methods, history of sentence embedding models, introduction to SentenceTransformers (origins, use cases), installation and first manipulations in Python, exploration of pre-trained models, visualization of embeddings, first similarity calculations.
Selection of pre-trained models according to tasks, fine-tuning of models on specific cases (custom datasets), dataset management, evaluation of embedding quality, tips for generating performant encodings. Practical exercises: adaptation of a model to a business corpus.
Implementation of semantic similarity search on a dataset, building a text search engine based on SentenceTransformers, coupling with FAISS for scalable indexing, text clustering by embeddings, integration into APIs and web applications, deployment best practices. Debriefing and perspectives.
Target audience
Developers, data scientists, and NLP professionals wishing to integrate SentenceTransformers into their projects
Prerequisites
Proficiency in Python and prior knowledge of NLP and machine learning
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