Iterative.ai Reviews

1. Ryan Raposo

   | Software Developer at Self-employed | over 3 years ago
   Rare

   The people at iterative.ai are special.

   Its hard to describe quickly, but if you're a potential client or employee--you could easily go your entire career unaware that groups like this exist.

   Their tools (like DVC) are exceptional, but I write this review because one need only interact with the people there to understand why they're execptional.

   The culture there is one that can only exist when the founding talent is top-tier. The experience you'll have, though, is so much more than that.

   Recommend whole-heatedly.

   🏁 Competitors: Git Large File Storage, Make.com, Workflow Management Software

   👍 Pros:    Constantly improving|Quality|Community

Scikit-learn Reviews

Iterative.ai mentions (6)

• Work with Google Drive files locally

  PyDrive2 is am open-source python package maintained by the awesome people at Iterative. And it is very easy to install:. - Source: dev.to / over 1 year ago

• Any MLOps platform you use?

  These three are made by Iterative.ai, and seem like very clean implementations of MLOps tooling - especially if you aren't dealing with massive data. https://iterative.ai/. Source: over 1 year ago

• How does your data science team collaborate?

  For what it's worth. (Full disclosure: I'm the community manager at Iterative (DVC,et.al.) Just wanted to make you aware of our online course (free) that we created specifically for Data Scientists (https://learn.iterative.ai). We know that bridging the gap between prototype to production/ jupyter notebook to reproducible/software engineering compatible, is a challenge. That's why we created the course. To also... Source: almost 2 years ago

• Advice about Infra and IaC

  What do you think of iterative.ai tools like dvc or cml? I have no direct experience, but I am looking at setting up something similar to what you need for a personal project. Source: almost 2 years ago

• TPI - Terraform provider for ML/AI & self-recovering spot-instances

  Hey all, we (at iterative.ai) are launching TPI - Terraform Provider Iterative https://github.com/iterative/terraform-provider-iterative. Source: about 2 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 / 3 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 / almost 1 year 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: about 1 year 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: about 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: over 1 year ago