Google Sheets + MonkeyLearn
Flookup
Textalytic
Causal for Google Sheets
Indico
SheetHacks by Polymer Search
Grist
Sheetlist
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
Exploratory
htm.java
Google Sheets + MonkeyLearn Scikit-learnNo Google Sheets + MonkeyLearn videos yet. You could help us improve this page by suggesting one.
Based on our record, Scikit-learn seems to be a lot more popular than Google Sheets + MonkeyLearn. While we know about 28 links to Scikit-learn, we've tracked only 1 mention of Google Sheets + MonkeyLearn. 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.
MonkeyLearn: MonkeyLearn is a powerful AI tool that automates text tagging in Google Sheets, eliminating manual and repetitive tasks. It is 100 times faster than human processing, significantly saving time, and 50 times more cost-effective. With MonkeyLearn, users can ensure consistent tagging criteria without errors, enabling efficient analysis of spreadsheets and faster insights from data. It offers direct... Source: 12 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
Flookup - Fuzzy lookup, highlight and remove duplicates from your datasets
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Textalytic - Free point & click text analysis in the browser
OpenCV - OpenCV is the world's biggest computer vision library
Causal for Google Sheets - Simulate 100s of scenarios without leaving your spreadsheet
NumPy - NumPy is the fundamental package for scientific computing with Python
