Frequently Asked Questions (FAQs)
Gadget is a powerful optimization tool that leverages an enhanced genetic algorithm via its extended PyGAD+ library to solve both single- and multi-objective optimization problems. Designed for general-purpose optimization, Gadget provides a secure, isolated environment for users to experiment with evolutionary techniques across various fields. It seamlessly integrates with popular libraries like Keras, PyTorch, and Scikit-Learn, making it ideal for training machine learning models and fine-tuning hyperparameters with ease.
Gadget features an intuitive interface with comprehensive charting tools to visualize the progress of the evolutionary process, including fitness, offering deep insights into the optimization journey. With a wide range of customizable parameters, users can tailor mutation rates, crossover types, selection methods, and more to meet their specific optimization needs. Additionally, Gadget can save the experiment to reproduce results efficiently or extend it later. Designed with flexibility and precision, Gadget is an essential tool for researchers, data scientists, and engineers tackling complex optimization challenges.
With a variety of ready-to-use applications that require no coding, Gadget makes it easy to get started with optimization tasks. These applications include hyperparameter optimization for popular machine learning models, a demo for solving the travelling salesman problem, 2D data clustering, and other optimization scenarios. Gadget’s library of applications is continuously expanding, with more use cases being added regularly.
For users looking to go beyond built-in options, Gadget supports custom code execution, enabling users to extend existing applications or address entirely new optimization challenges. This flexibility allows users to seamlessly integrate their own functions, models, or datasets, tailoring Gadget to fit unique requirements across various domains.
Gadget provides a trial period that includes some limitations compared to the full version, allowing users to explore its features and capabilities. If your trial period has ended and you believe you need additional time to evaluate Gadget, please don't hesitate to reach out to us. We're happy to assist you and discuss options for extending your trial so you can make the most informed decision about our tool.
No, Gadget does not currently offer an API (Application Programming Interface). However, this feature is on the roadmap for future development and support.
To continue executing an already-run submission for an additional X generations, ensure that the 'Save Code' option was enabled in the app settings before you ran the original submission. If so, there will be an option to continue executing the submission.
Yes, there is a 'Save Code' option in the app settings that controls whether code is saved. It’s enabled by default, but if disabled, any user-defined code is only used for executing the submission and is then discarded.
You can cancel your subscription at any time by visiting the Billing page and clicking 'Cancel Subscription' to schedule the cancellation.
Once you initiate the cancellation of your subscription, it is scheduled for cancellation but remains active until the end of your current subscription period. After this period concludes, the subscription will be canceled, and no further payments will be processed.
During the grace period, you have the option to reactivate your subscription at any time before the current subscription period ends. Reactivating will resume normal payment processing.
No, we do not store your card or bank information. All payments are processed securely using the Stripe platform.
We aim to include a wide range of Python libraries, making it easy for you to import them directly into your code. However, some libraries might not be pre-installed in our environment. If you need a specific library that isn't available, please don't hesitate to contact us.
