To reach your growth goals, you need better copy. More stories. Faster. We can help you get there. And we'll help you become a better storyteller along the way.
StoryLab.ai is an online tool that generates content ideas for you, and then helps you along the writing process by generating hooks and outlines for your stories.
We also offer ready-made copy for your marketing purposes. The AI part of our product is a direct link to GPT-3, the most powerful Natural Language Processing AI available in the market.
Our content and template library together with our tool, not only help you generate more content faster: using them makes you a better and more effective storyteller.
Write more. Write better. Grow faster. StoryLab.ai
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Based on our record, Scikit-learn seems to be a lot more popular than StoryLab.ai. While we know about 28 links to Scikit-learn, we've tracked only 1 mention of StoryLab.ai. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
StoryLab.ai is an AI copy generator that helps you come up with ideas for your stories & marketing Content faster. Source: almost 3 years ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
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