Learn to evaluate the performance of our models (with most relevant technique, k-Fold Cross Validation) and improve them with effective Parameter Tuning Understand the intuition behind Artificial Neural Networks, Convolutional Neural Networks and Recurrent Neural Networks Understand Self-Organizing Maps and...
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$schema: https://azuremlschemas.azureedge.net/latest/managedOnlineDeployment.schema.json name: blue endpoint_name: my-endpoint model: path: ../../model-1/model/ code_configuration: code: ../../model-1/onlinescoring/ scoring_script: score.py environment: conda_file: ../../model-1/enviro...
In a new paper Upcycling Large Language Models into Mixture of Experts, an NVIDIA research team introduces a new “virtual group” initialization technique to facilitate the transition of dense models into fine-grained MoE structures. 2024-10-123 ...
AAAI Ext-Sub [Code] LLM Feature Unlearning for Pre-trained GANs and VAEs 2024 Moon et al. AAAI - - GAN, VAEs Multi-Modal Recommendation Unlearning 2024 Sinha et al. arXiv MMRecUN - recommendation system Preserving Privacy Through Dememorization: An Unlearning Technique For Mitigating Memorizati...
Multiplelinear regression(MLR) is a regression algorithm that describes the linear connection between adependent variableand several independent variables. Each feature variable must represent the linear relation between the dependent and independent variables.MLRaims to fit a regression line in a multidimen...
Evolutionary computation, for example, particle swarm optimization, has impressive achievements in solving complex problems in science and industry; however, an important open problem in evolutionary computation is that there is no theoretical guarantee
IBM watsonx.ai Train, validate, tune and deploy generative AI, foundation models and machine learning capabilities with IBM watsonx.ai, a next-generation enterprise studio for AI builders. Build AI applications in a fraction of the time with a fraction of the data. ...
Regression is used to understand the relationship between dependent and independent variables. It is commonly used to make projections, such as sales revenue for a given business. Linear regression, logistical regression, and polynomial regression are popular regression algorithms. Various algorithms and ...
The dependent variable value is in the last column. After creating the 1,000 data items, the data set was randomly split into an 800-item training set to be used to find the model b-weights, and a 200-item test set to be used to evaluate the quality of the resulting model....