Keboola
Pentaho
Matillion
Talend
Microsoft Power BI
Fivetran
Talend Data Integration
CloverDX
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
Exploratory
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Keboola enables data engineers, analysts, and engineers to collaborate on analytics and automation as a team, from extraction, transformation, data management, and pipeline orchestration to reverse ETL. Keboola provides a cloud-based data integration platform to support the entire workflow from data extraction, cleaning, warehousing, and enrichment, to ML-based predictions and loading. The platform is highly collaborative and solves the most significant hurdles of "IT" based solutions. Try us out! You will love the experience :)
Keboola Scikit-learnI can't imagine working with data in our company without Keboola at the moment. Within a few minutes, I can set up a project and start work with data. Thanks to the simple interface, even a non-data person can work with Keboola. Keboola is an incredible time-saver.
Based on our record, Scikit-learn seems to be a lot more popular than Keboola. While we know about 27 links to Scikit-learn, we've tracked only 2 mentions of Keboola. 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.
I'll throw our hat in the ring. Keboola. Source: 10 months ago
Keboola.com - They have a free tier with "built-in" Snowflake so would be the most cost-effective option but wouldn't choose them if you go down the GBQ route. Source: about 1 year 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: 12 months 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
This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
Pentaho - Pentaho is a Business Intelligence software company that offers Pentaho Business Analytics, a suite...
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Matillion - Matillion is a cloud-based data integration software.
OpenCV - OpenCV is the world's biggest computer vision library
Talend - Talend Cloud delivers a single, open platform for data integration across cloud and on-premises environments. Put more data to work for your business faster with Talend.
NumPy - NumPy is the fundamental package for scientific computing with Python