Improvado.io VS Scikit-learn

Compare Improvado.io VS Scikit-learn and see what are their differences

LiveSession

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Improvado.io

Improvado is an ETL platform that extracts data from 300+ pre-built connectors, transforms it, and seamlessly loads the results to wherever you need them. No more Tedious Manual Work, Errors or Discrepancies. Contact us for a demo.

Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Landing page //
2023-08-31

Consolidate all your marketing data in one place to get better business insights. Speed up your decision-making process and quickly implement optimizations without wasting time crunching the data. Real-time reports & dashboards eliminate manual reporting time by 90%. That’s what’ve done before for Ancestry, Asus, AdRoll and we can do it for you. Collaborate effectively with your team, other departments, and stakeholders. No more Tedious Manual Work, Errors or Discrepancies. Book a demo now at improvado.io

Landing page //
2022-05-06

Improvado.io

Website: improvado.io
Pricing URL: Official Improvado.io Pricing
$ Details: paid
Platforms: Web Cloud REST API Browser
Release Date: 2015 April
Categories: #Marketing #Marketing Analytics #Data Extraction #Data Integration #ETL #Predictive Analytics #Data Pipelines

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Scikit-learn

Website: scikit-learn.org
Pricing URL: -
$ Details
Platforms: -
Release Date: -
Categories: #Data Science And Machine Learning #Data Science Tools #Python Tools #Software Libraries

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Improvado.io features and specs

Data Extraction and Loading: Integrate and manage data from 300+ sources
Data Transformation: Make your marketing data analysis-ready
Marketing Common Data Model: Automate cross-channel normalization
Professional Services: Yes
Managed Services: Managed Data Warehouse
Data Synchronization: Yes
Managed API: Managed data sources API
Data Pipeline Orchestration: Yes
Customizable: Yes
Customer Support: 24/7
Visualizations: Yes
Extraction templates: Yes

Scikit-learn features and specs

No features have been listed yet.

Improvado.io videos

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How to Leverage Data to Drive Massive Revenue - Sponsored by Improvado.io

Scikit-learn videos

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Learning Scikit-Learn (AI Adventures)

Category Popularity

0-100% (relative to Improvado.io and Scikit-learn)

Improvado.io

Scikit-learn

Marketing

100 100%

Marketing

0% 0

Data Science And Machine Learning

0 0%

Data Science And Machine Learning

100% 100

Data Integration

100 100%

Data Integration

0% 0

Data Science Tools

0 0%

Data Science Tools

100% 100

User comments

Share your experience with using Improvado.io and Scikit-learn. For example, how are they different and which one is better?

Reviews

These are some of the external sources and on-site user reviews we've used to compare Improvado.io and Scikit-learn

Improvado.io Reviews

Funnel.io Alternatives and Competitors in 2022

The Improvado platform is specifically focused on the marketing dilemma and will connect to any marketing platform you need. The integrations run deep, pulling in granular data from the keyword and ad level, to allow you to see the complete picture. It’s a great tool for marketing analysts, performance marketers, and managers of all levels, who use marketing data on a daily...

Source: improvado.io

15 Best ETL Tools in 2022 (A Complete Updated List)

Improvado is a data analytics software for marketers to help them keep all their data in one place. This marketing ETL platform will allow you to connect marketing API to any visualization tool and for that no need to have technical skills.

Source: www.softwaretestinghelp.com

Top 5 Supermetrics Alternatives – Competitors, Cost, Features & Pricing Model

Improvado has a strong 4.5/5 on G2 with people not complaining much about anything. In cons, the high pricing was mentioned but considered reasonable with the level of support Improvado gives.

Source: windsor.ai

Domo vs Datorama vs Improvado vs Funnel.io vs Supermetrics

The biggest benefit I see for improvado.io is that their customer service reps are included in every package and are highly attentive. They'll help you build out custom dashboards and integrations to ensure that you're visualizing your data in exactly the way you need it.

Source: improvado.io

Scikit-learn Reviews

15 data science tools to consider using in 2021

Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 27 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.

Improvado.io mentions (0)

We have not tracked any mentions of Improvado.io yet. Tracking of Improvado.io recommendations started around Mar 2021.

Scikit-learn mentions (27)

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: 12 months 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
Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
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