Model: datasocietyco/bge-base-en-v1.5-course-recommender-v1
Author: datasocietyco
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:183, loss:MultipleNegativesRankingLoss, arxiv:1908.10084, arxiv:1705.00652, base_model:BAAI/bge-base-en-v1.5, base_model:finetune:BAAI/bge-base-en-v1.5, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: BAAI/bge-base-en-v1.5
Card metadata: base_model: BAAI/bge-base-en-v1.5
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:183, loss:MultipleNegativesRankingLoss
widget: source_sentence: Introduction to Network Protocols
sentences: Introduction to Network Protocols A course that builds foundational knowledge of network protocols essentially covering emails and other internet protocols Course language: TBD Prerequisite course required: Introduction to Managing Servers Professionals who would like to get foundational knowledge of basic network protocols, Course language: TBD, Prerequisite course required: Introduction to Managing Servers, A course that builds foundational knowledge of network protocols essentially covering emails and other internet protocols, Professionals who would like to get foundational knowledge of basic network protocols, source_sentence: Optimizing Ensemble Methods
sentences: Course language: Python, Prerequisite course required: Ensemble Methods, This course covers advanced topics in optimizing ensemble learning methods – specifically random forest and gradient boosting. Students will learn to implement base models and perform hyperparameter tuning to enhance the performance of models., Professionals experience in ensemble methods and who want to enhance their skill set in advanced Python classification techniques., Optimizing Ensemble Methods This course covers advanced topics in optimizing ensemble learning methods – specifically random forest and gradient boosting. Students will learn to implement base models and perform hyperparameter tuning to enhance the performance of models. Course language: Python Prerequisite course required: Ensemble Methods Professionals experience in ensemble methods and who want to enhance their skill set in advanced Python classification techniques., source_sentence: Autoencoders
sentences: Professionals some Python experience who would like to expand their skillset to more advanced machine learning algorithms for image processing and computer vision., Prerequisite course required: Convolutional Neural Networks (CNN) for Image Recognition, Course language: Python, Autoencoders This course takes students through a journey into the world od autoencoders - a set of powerful deep learning models that have a special place in the world of image analysis. By the end of this course students will be able to navigate through the application space of autoencoders and implement autoencoders to perform tasks such as image denoising and more. Course language: Python Prerequisite course required: Convolutional Neural Networks (CNN) for Image Recognition Professionals some Python experience who would like to expand their skillset to more advanced machine learning algorithms for image processing and computer vision., This course takes students through a journey into the world od autoencoders - a set of powerful deep learning models that have a special place in the world of image analysis. By the end of this course students will be able to navigate through the application space of autoencoders and implement autoencoders to perform tasks such as image denoising and more., source_sentence: Authentication Python
sentences: Prerequisite course required: Basic GraphQL: Python, Authentication Python An introduction to Authentication concepts and how it can be implemented using Python. Course language: Python Prerequisite course required: Basic GraphQL: Python Professionals who would like to learn the core concepts of authentication using Python., An introduction to Authentication concepts and how it can be implemented using Python., Course language: Python, Professionals who would like to learn the core concepts of authentication using Python., source_sentence: Clustering in NLP
sentences: Clustering in NLP This course covers the clustering concepts of natural language processing, equipping learners with the ability to cluster text data into groups and topics by finding similarities between different documents. Course language: Python Prerequisite course required: Topic Modeling in NLP This is an intermediate level course for data scientists who have some experience with NLP and want to learn to cluster textual data., Course language: Python, Prerequisite course required: Topic Modeling in NLP, This course covers the clustering concepts of natural language processing, equipping learners with the ability to cluster text data into groups and topics by finding similarities between different documents., This is an intermediate level course for data scientists who have some experience with NLP and want to learn to cluster textual data.
Likes: 0 | All-time downloads: 234
Created: 2024-10-07 12:28:14