Scikit-learn VS ShoutOUT

Scikit-learn Reviews

ShoutOUT Reviews

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   over 4 years ago

Scikit-learn mentions (28)

• How to Build a Logistic Regression Model: A Spam-filter Tutorial

  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 / 2 months ago

• Link Prediction With node2vec in Physics Collaboration Network

  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

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  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: 12 months ago

• PSA: You don't need fancy stuff to do good work.

  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: almost 1 year ago

• Help on using R for Machine Learning?

  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

ShoutOUT mentions (5)

• Why we switched from docker to serverless

  Here at ShoutOUT, we’ve been happily operating on Amazon Web Services for years. But there is always room for improvement. Luckily, we have the kind of team that doesn’t hesitate to embrace new technologies that will improve the platform-and that’s the very reason why we decided to try serverless architecture. - Source: dev.to / about 2 years ago

• SMS Platform - Apps for integrations

  As the next step of ShoutOUT (https://getshoutout.com/) we are going to add integrations to the platform. I would like to know your preferred apps integrate with our SMS platform. Source: about 2 years ago

• How should I validate my product in the US market?

  Hey folks, I am building a business texting tool (https://getshoutout.com/) It’s not built for a very specific market. Product is pretty general in this space. Source: over 2 years ago

• Looking for feedback on a business texting SaaS product

  Hey Community, we are launching a business texting tool in the US market. You can test our product from anywhere in the world. We appreciate it if you would like to give any feedback on our website content, product onboarding, UI/UX, etc. - https://getshoutout.com/. Source: over 2 years ago

• I am building a SaaS product from outside US. but I want to scale my product in the US market.

  Thanks a lot for the comments! I have already registered the company in the US market. We started Google CPC campaigns with a smaller budget. Yes, we are seeing users registering now. But they are hardly converting to a paid customer.(We are doing well in my market) If you are curious here’s my SaaS product- https://getshoutout.com. Source: over 2 years ago