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  1. Stackups
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  5. Dasha vs Kaggle

Dasha vs Kaggle

OverviewComparisonAlternatives

Overview

Dasha
Dasha
Stacks3
Followers8
Votes0
Kaggle
Kaggle
Stacks10
Followers7
Votes0

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Detailed Comparison

Dasha
Dasha
Kaggle
Kaggle

Dasha is a conversational AI as a Service platform. Dasha lets you create conversational apps that are more human-like than ever before, quicker than ever before and quickly integrate them into your products.

Machine learners share, stress test, and stay up-to-date on all the latest ML techniques and technologies. Discover a huge repository of community-published models, data & code for your next project.

Declarative language for conversation design; VSCode extension; native STT, NLP, NLU, NLG and TTS; Support for external TTS; Voice over SIP Trunk; Node.js SDK; Voice over GRPC; Text over GRPC; API-first; Open developer platform; Unlimited conversational depth; High conversational concurrency; Robust digressions and intents for the human-like experience; Custom intents training
Find all the resources and knowledge needed for your next real-world ML project; High-quality public datasets. Everything from avocado prices to video game sales; Public notebooks and access to a powerful notebook environment with no cost GPUs & TPUs; Pre-trained, ready-to-deploy ML models; Build your ML skills in a supportive and helpful community
Statistics
Stacks
3
Stacks
10
Followers
8
Followers
7
Votes
0
Votes
0
Integrations
Node.js
Node.js
Visual Studio Code
Visual Studio Code
Jupyter
Jupyter
Python
Python

What are some alternatives to Dasha, Kaggle?

rasa NLU

rasa NLU

rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

NumPy

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

SpaCy

SpaCy

It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.

Inferrd

Inferrd

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

PyXLL

PyXLL

Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!

Speechly

Speechly

It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.

GraphLab Create

GraphLab Create

Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

MonkeyLearn

MonkeyLearn

Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.

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