Based on our record, Kotlin should be more popular than Scikit-learn. It has been mentiond 75 times since March 2021. 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.
For the rest of this post I’ll list off some more tactical examples of things that you can do towards this goal. Savvy readers will note that these are not novel ideas of my own, and in fact a lot of the things on this list are popular core features in modern languages such as Kotlin, Rust, and Clojure. Kotlin, in particular, has done an amazing job of emphasizing these best practices while still being an... - Source: dev.to / 5 days ago
A basic understanding of Kotlin and programming in general (OOP). - Source: dev.to / about 1 month ago
Being somewhat allergic to coding in Java (this is a personal thing, if you like Java then good for you) I decided to try out writing the code using Kotlin from JetBrains instead. I'm already using IntelliJ as I work with Apache Spark using Scala, so the tooling was already there and ready to go for this. - Source: dev.to / about 2 months ago
Congrats to our friends at Kotlin. 🚀 After years of growth and development, KMP reaches a pivotal milestone with 1.9.20. We’ve been on team Kotlin Multiplatform since day one, and the best is yet to come! Learn more 👉 https://touchlab.co/kotlin-multiplatform-is-stable. Source: 6 months ago
Another option could be to check out Kotlin. It's a JVM language that while still object-oriented has may functional syntax features. Source: 7 months 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 / 2 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: 12 months 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
Dart - A new web programming language with libraries, a virtual machine, and tools
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
OpenCV - OpenCV is the world's biggest computer vision library
Elixir - Dynamic, functional language designed for building scalable and maintainable applications
NumPy - NumPy is the fundamental package for scientific computing with Python