In February 2024, the team at TensorFlow announced that, for the time being at least, they're closing the official TensorFlow Certificate exam while they 'evaluate the next step' in the certificate program. For those who registered for the exam before April 30, 2024, you had until May 31,...
Advanced. Large-scale projects like a full-stack web application, a complex data analysis project, or a deep learning model usingTensorFloworPyTorch. We’ve got a full guide onhow to build a great data science portfolio, which covers a variety of different examples. And don’t forget; you ...
TensorFlow Tuning shows how to use SageMaker hyperparameter tuning with the pre-built TensorFlow container and MNIST dataset. MXNet Tuning shows how to use SageMaker hyperparameter tuning with the pre-built MXNet container and MNIST dataset. HuggingFace Tuning shows how to use SageMaker hyperparameter...
As shown in the table, removing the word “lazy” decreased the predicted negative score to zero, while all other perturbations had a negligible effect on the predictions made by the model. The idea is to fit an interpretable model (such as a decision tree or a linear regression) on the ...
Learn what is fine tuning and how to fine-tune a language model to improve its performance on your specific task. Know the steps involved and the benefits of using this technique.
Select the appropriate machine learning algorithms and techniques for training your personal assistant’s AI model. This may involve using techniques like supervised learning, unsupervised learning, or reinforcement learning. Split your data into training and testing sets to evaluate the model’s performan...
How can I calculate the precision and recall for my model? And: How can I calculate the F1-score or confusion matrix for my model? In this tutorial, you will discover how to calculate metrics to evaluate your deep learning neural network model with a step-by-step example. After comp...
Assess their proficiency in programming languages and AI frameworks, as well as their understanding of machine learning, to gauge their technical capabilities for handling your AI projects. Present real-world AI scenarios to evaluate their critical thinking, problem-solving skills, and ability to naviga...
Selecting the best prompt is an empirical process. Test your prompts with the model and evaluate the results. Adjust as needed, and iterate until you are satisfied with the output. Select Appropriate Model Configuration Selecting the appropriate model and adjusting hyper-parameters are crucial factors...
It provides a unified interface to hundreds of ML algorithms, making it easier to train models, make predictions, and evaluate their performance, all within a consistent framework. Machine Learning With caret in R randomForest This package implements the random forest algorithm, known for its ...