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MonkeyLearn
Conheça MonkeyLearn
O MonkeyLearn é uma plataforma de inteligência artificial que permite analisar o texto com aprendizado de máquina para automatizar fluxos de trabalho de negócios e economizar horas de processamento manual de dados.
Clientes como Clearbit, Segment e Drift usam o MonkeyLearn para classificar e extrair dados acionáveis de textos brutos como e-mails, chats, páginas da Internet, documentos, tweets e muito mais!
O MonkeyLearn pode ser facilmente integrado por meio de integrações com planilhas Google, o Zapier, o Zendesk ou o Rapidminer (não é necessário codificação) ou através dos APIs e SDKs.
Quem usa MonkeyLearn?
Pequenas e médias empresas que precisam transformar texto em dados acionáveis. Os usuários variam de profissionais de marketing a vendedores, equipes de suporte ao cliente, analistas de dados, desenvolvedores, entre outros.
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Avaliações do MonkeyLearn
Best platform for implementing machine learning
Comentários: The main problem it has helped in solving through is the decrease in work load that was required earlier and at the same time increasing the efficiency and rate of accuracy.
Vantagens:
It provides a great user-interface and is flexible. It has a well-documented API that is also very user-friendly. It has provided tutorials that turns handy when required. It is contaminated with many models for performing various tasks like text analysis. At the same time, it is also easy to use.
Desvantagens:
There is a limitation provided on the number of queries one can make as per their current plan. But that is still not an issue as it does not affect much to the overall development and functionality of the software.
Varieties of text analytics APIs can be found in Monkeylearn only! The best of the best...
Comentários: A good platform/software with common analysis and variety of sentiment analysis.
Vantagens:
I liked mostly 1) The process of data scrapping (build), process (run), and analysis (analytics) is very simple and user-friendly. 2) Sample templates for Zoom and Netflix are provided to get the taste of the generic text analysis
Desvantagens:
They are in all places. Innovation in the analysis is required and seen less in the platform.
MonkeyLearn Review for Final Project
Comentários: My overall experience with the tool "MonkeyLearn" was helpful and it helped me in getting the sentiment analysis + keyword analysis done efficiently. I used the results obtained thus through this tool for use in my other projects as Raw data (input data). This tool is very easy to use and comes with a self-learning experience. It is one of the by far best sentiment analysis tools I have used so far and it gives you a classification of up to 75% correct sentiment classification of your input data as compared to actual classification.
Vantagens:
, and neutral sentiments along with the confidence scores. I created my own classifier too for one of my projects where I was able to use my model to train the rest of my data. I further used the keyword + sentiment analysis template to generate tags and classification of input data. this helped me get sentiment analysis and the keywords extraction from the template. Further, the platform gives us visualization in form of colored positive, negative, and neutral classification of input text data. the tool provides a word cloud which is helpful to understand the important keywords occurring most frequently.
Desvantagens:
There are very less things or say not any as such that I didn't like about this software. However, I can state a few of the things that I felt can enhance a user experience while starting to use this software and might can help in improving the decision to buy this tool as paid subscription as follows. Firstly, it is great to have used the trial version of any such platform which allows us to use try and test the platform. This tool allows us to use this platform for free by creating a login. I would have been happier to have allowed more than 1K of input rows of data that is allowed in the free version as nowadays we are generally using really large files of datasets, especially when using text or sentiment analysis the dataset is generally large. So if by any chance the tool could provide a new user to use the platform by not limiting the count of rows to be classified but rather letting them use the platform for free for a limited set of free days would help and enable the user to take decision more effectively. Another reason for this is sometimes we might want to rerun a data set using some other column or additional column of data as input to the classifier, and so on. but in the case of having a fixed 1K rows allowed, we cannot actually use the platform to its full potential to test the platform.
Amazing support team and user interface!
Vantagens:
this software is super easy to use and makes ML algorithms honestly a total piece of cake to create - I'm not even sure how to code. So this is an awesome service, and I've really enjoyed it. PLUS their support is phenomenal. Way above and beyond
Desvantagens:
It's a little bit pricey, but that is because there is no coding, hosting, or any of the complex stuff normally associated with deploying a machine learning algorithm
