Tag Archives: Salesforce Einstein

Recurrent Neural Network Applications with Long Short-Term Memory

What is a Neuron?

In Biological term, Neurons is the unit of nervous system which is responsible for flow of message in the form of electrical impulse in Human brain. So, Neuron is responsible for Human intelligence. But, in Today’s scenario it is used in Artificial Intelligence as well. Recurrent Neural Network Application is a class of Artificial neural network in which connections between the neurons form a directed graph, or in simpler words, having a self-loop in the hidden layers. This helps RNNs to utilize the previous state of the hidden neurons to learn current state. Along with the current input, RNNs utilize the information they have learnt previously. Among all the neural networks, they are the only one with an internal memory. A usual RNN has a short-term memory. Because of their internal memory, RNN are able to remember things.

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Posted in Salesforce, Salesforce AI. Tagged with , , , , .

Use TransmogrifAI Python to jumpstart Salesforce machine learning

Salesforce released TransmogrifAI Python, a machine learning library written in Scala that runs on top of Spark. This can be potentially deployed on any cloud such as Heroku/PostgreSQL platform. What all is involved in TransmogrifAI python?

  • Language: Scala
  • Underlying engine: Apache Spark data processing engine
  • Deployment platform: A standalone local machine or cloud platform like Heroku

Let us explore a bit more about these new players in the scene and whether they will align with our need to build robust machine learning models. The entry barrier to using the TransmogrifAI python library is likely to be the new tech stack that a typical Salesforce developer needs to scale up to.

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Posted in Salesforce Machine Learning. Tagged with , , .

Playing with the Salesforce Sentiments Analysis

People have always had an interest in what other people think, or what opinion they hold. Since the inception of the internet, increasing numbers of people are using websites and social media platform for expressing their opinion. Due to platforms such as Facebook, Twitter etc., it has become feasible to analyze and extract the public opinion on a certain topic, news story, product, or brand.

Opinions that are mined from such services can be valuable. Data mined from these sources can be analyzed and presented accordingly to easily identify the online mood (positive, negative or neutral). This allows individuals or business to be proactive as opposed to reactive when a negative conversational thread is emerging. Alternatively, positive sentiments can be leveraged to identify product advocates as well to shape the business strategy by seeing the parts of the strategy that are working.

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