Malcolm App VS TensorFlow
Compare Malcolm App VS TensorFlow and see what are their differences
Holistic service management: service, support + customer care. From Ticketing to Helpdesk, Service Desk, ITSM to Enterprise Service Management
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Malcolm App
HelpDocs
Typeform
Zendesk Support
HelpJuice
HelpScout
Jotform
Wufoo
TensorFlow
PyTorch
Keras
Scikit-learn
OpenCV
IBM Watson Studio
Amazon SageMaker
Pega Platform
Our powerful, flexible and easy to use no-code platform lets you quickly digitise your routine customer service related tasks, customer journeys, actions, follow-ups, questions, knowledge & policies. Then surface these to your customers via a dedicated self-service portal or by using our embeds which enable you to bring content and self-service functionality from Malcolm! into your existing websites, apps or products.
Malcolm App TensorFlowNo features have been listed yet.
Malcolm App's answer
The product is more powerful
Malcolm App's answer
Since 2003 we’ve been designing, building and operating bespoke customer servicing focused systems for companies and organisations around the world. We’ve seen first hand the positive and transformative effect these systems deliver to our clients and their users. We’ve learnt a lot along the way about how best to design such systems and the features and technical approaches that make things stable, robust and usable. It has long been an ambition of ours to create a powerful, flexible and easy to use SaaS product available at a very competitive price. Malcolm! is that ambition realised. We hope that businesses large and small, all over the world, will use Malcolm! to make their own business better.
Malcolm App's answer
Malcolm App's answer
Our combination of features and the teams experience of building customer servicing systems (for over 20 years!)
Malcolm App's answer
Companies and/or organisations who have a high and growing level of customer service activity
Malcolm App's answer
Based on our record, TensorFlow seems to be more popular. It has been mentiond 7 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.
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 1 year ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 2 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 2 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 2 years ago
HelpDocs - Educate your users with a super simple knowledge base that’s built for teams just like yours.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Typeform - Create beautiful, next-generation online forms with Typeform, the form & survey builder that makes asking questions easy & human on any device. Try it FREE!
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Zendesk Support - Social Customer Support and Help Desk and Ticketing
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.