Complete Guide to Building a Chatbot with Deep Learning

With spaCy for entity extraction, Keras for intent classification, and more!

Over the past month, I wanted to look for a project that encompasses the entire data science end-to-end workflow — from the data pipeline, to deep learning, to deployment. It had to be challenging, but not pointlessly so — it still had to be something useful. It took a little ideation and divergent thinking, but when the idea of making a personal assistant came up, it didn’t take long for me to settle on it. Conversational assitants are everywhere. Even my university is currently using Dr. Chatbot to track the health status of its members as an effective way to monitor this current pandemic. And it just makes sense: chatbots are faster, easier to interact with, and is super useful especially for things that we just want a fast response on. In this day and age, being able to talk to a bot for help is starting to become the new standard. I personally believe bots are the future because they just make our lives so much easier. Chatbots are also a key component in Robotic Process Automation.

Now I want to introduceEVE bot, my robot designed to Enhance Virtual Engagement (see what I did there) for the Apple Support team on Twitter. Although this methodology is used to support Apple products, it honestly could be applied to any domain you can think of where a chatbot would be useful.

Here’s my demo video for EVE. (And here’s my Github repo for this project)

#nlp #named-entity-recognition #deep-learning #chatbots #customer-service #complete guide to building a chatbot with deep learning

Complete Guide to Building a Chatbot with Deep Learning

Complete Guide to Building a Chatbot with Deep Learning

With spaCy for entity extraction, Keras for intent classification, and more!

Over the past month, I wanted to look for a project that encompasses the entire data science end-to-end workflow — from the data pipeline, to deep learning, to deployment. It had to be challenging, but not pointlessly so — it still had to be something useful. It took a little ideation and divergent thinking, but when the idea of making a personal assistant came up, it didn’t take long for me to settle on it. Conversational assitants are everywhere. Even my university is currently using Dr. Chatbot to track the health status of its members as an effective way to monitor this current pandemic. And it just makes sense: chatbots are faster, easier to interact with, and is super useful especially for things that we just want a fast response on. In this day and age, being able to talk to a bot for help is starting to become the new standard. I personally believe bots are the future because they just make our lives so much easier. Chatbots are also a key component in Robotic Process Automation.

Now I want to introduceEVE bot, my robot designed to Enhance Virtual Engagement (see what I did there) for the Apple Support team on Twitter. Although this methodology is used to support Apple products, it honestly could be applied to any domain you can think of where a chatbot would be useful.

Here’s my demo video for EVE. (And here’s my Github repo for this project)

#nlp #named-entity-recognition #deep-learning #chatbots #customer-service #complete guide to building a chatbot with deep learning

Complete Guide to Building a Chatbot with Deep Learning

Top Deep Learning Development Services | Hire Deep Learning Developer

View more: https://www.inexture.com/services/deep-learning-development/

We at Inexture, strategically work on every project we are associated with. We propose a robust set of AI, ML, and DL consulting services. Our virtuoso team of data scientists and developers meticulously work on every project and add a personalized touch to it. Because we keep our clientele aware of everything being done associated with their project so there’s a sense of transparency being maintained. Leverage our services for your next AI project for end-to-end optimum services.

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Top Deep Learning Development Services | Hire Deep Learning Developer
Mikel  Okuneva

Mikel Okuneva

1603735200

Top 10 Deep Learning Sessions To Look Forward To At DVDC 2020

The Deep Learning DevCon 2020, DLDC 2020, has exciting talks and sessions around the latest developments in the field of deep learning, that will not only be interesting for professionals of this field but also for the enthusiasts who are willing to make a career in the field of deep learning. The two-day conference scheduled for 29th and 30th October will host paper presentations, tech talks, workshops that will uncover some interesting developments as well as the latest research and advancement of this area. Further to this, with deep learning gaining massive traction, this conference will highlight some fascinating use cases across the world.

Here are ten interesting talks and sessions of DLDC 2020 that one should definitely attend:

Also Read: Why Deep Learning DevCon Comes At The Right Time


Adversarial Robustness in Deep Learning

By Dipanjan Sarkar

**About: **Adversarial Robustness in Deep Learning is a session presented by Dipanjan Sarkar, a Data Science Lead at Applied Materials, as well as a Google Developer Expert in Machine Learning. In this session, he will focus on the adversarial robustness in the field of deep learning, where he talks about its importance, different types of adversarial attacks, and will showcase some ways to train the neural networks with adversarial realisation. Considering abstract deep learning has brought us tremendous achievements in the fields of computer vision and natural language processing, this talk will be really interesting for people working in this area. With this session, the attendees will have a comprehensive understanding of adversarial perturbations in the field of deep learning and ways to deal with them with common recipes.

Read an interview with Dipanjan Sarkar.

Imbalance Handling with Combination of Deep Variational Autoencoder and NEATER

By Divye Singh

**About: **Imbalance Handling with Combination of Deep Variational Autoencoder and NEATER is a paper presentation by Divye Singh, who has a masters in technology degree in Mathematical Modeling and Simulation and has the interest to research in the field of artificial intelligence, learning-based systems, machine learning, etc. In this paper presentation, he will talk about the common problem of class imbalance in medical diagnosis and anomaly detection, and how the problem can be solved with a deep learning framework. The talk focuses on the paper, where he has proposed a synergistic over-sampling method generating informative synthetic minority class data by filtering the noise from the over-sampled examples. Further, he will also showcase the experimental results on several real-life imbalanced datasets to prove the effectiveness of the proposed method for binary classification problems.

Default Rate Prediction Models for Self-Employment in Korea using Ridge, Random Forest & Deep Neural Network

By Dongsuk Hong

About: This is a paper presentation given by Dongsuk Hong, who is a PhD in Computer Science, and works in the big data centre of Korea Credit Information Services. This talk will introduce the attendees with machine learning and deep learning models for predicting self-employment default rates using credit information. He will talk about the study, where the DNN model is implemented for two purposes — a sub-model for the selection of credit information variables; and works for cascading to the final model that predicts default rates. Hong’s main research area is data analysis of credit information, where she is particularly interested in evaluating the performance of prediction models based on machine learning and deep learning. This talk will be interesting for the deep learning practitioners who are willing to make a career in this field.


#opinions #attend dldc 2020 #deep learning #deep learning sessions #deep learning talks #dldc 2020 #top deep learning sessions at dldc 2020 #top deep learning talks at dldc 2020

Top 10 Deep Learning Sessions To Look Forward To At DVDC 2020

The Best Way to Build a Chatbot in 2021

A useful tool several businesses implement for answering questions that potential customers may have is a chatbot. Many programming languages give web designers several ways on how to make a chatbot for their websites. They are capable of answering basic questions for visitors and offer innovation for businesses.

With the help of programming languages, it is possible to create a chatbot from the ground up to satisfy someone’s needs.

Plan Out the Chatbot’s Purpose

Before building a chatbot, it is ideal for web designers to determine how it will function on a website. Several chatbot duties center around fulfilling customers’ needs and questions or compiling and optimizing data via transactions.

Some benefits of implementing chatbots include:

  • Generating leads for marketing products and services
  • Improve work capacity when employees cannot answer questions or during non-business hours
  • Reducing errors while providing accurate information to customers or visitors
  • Meeting customer demands through instant communication
  • Alerting customers about their online transactions

Some programmers may choose to design a chatbox to function through predefined answers based on the questions customers may input or function by adapting and learning via human input.

#chatbots #latest news #the best way to build a chatbot in 2021 #build #build a chatbot #best way to build a chatbot

The Best Way to Build a Chatbot in 2021
Erwin  Boyer

Erwin Boyer

1624498185

AI Chatbots for Business: Why You Need One Now!

It’s said that Artificial Intelligence will be just as smart as humans by 2050. Experts like Ray Kurzweil have even predicted that we’ll achieve a technological singularity by 2045.

From that point on, it’s believed that AI will start inventing Nobel Prize-winning inventions every 5 minutes. Granted it’s gonna be out of our control, but hey, at least we’ll see a revolutionary breakthrough.

We may think that these claims are outlandish and ridiculous, but if someone were to tell me in the 70s that there will be self-driving cars in the future, I would’ve wanted to smoke whatever they were smoking.

But guess what, here we are in 2020, and Tesla already has their self-driving cars on the roads right now. And these were all recently developed technologies. Did you know that the first chatbot was actually launched in 1966?

Features of AI Chatbots

Why Do You Need an AI Chatbot?

Chatbots Across Various Industries

Wrapping Up

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AI Chatbots for Business: Why You Need One Now!