Tuesday, September 15Digital Marketing Journals

Tag: choice

Why MMS Marketing is a good choice | by Cloud Ladder Consulting | Dec, 2021
ai bot, ai chat, ai chatbot, best chatbot, chatbot, chatbot ai, chatbot app, chatbot online, chatbot website, cloud-ladder-consulting, cloud-messaging, conversation with ai, creating chatbots, Marketing, mass-texting, mms-marketing, robot chat

Why MMS Marketing is a good choice | by Cloud Ladder Consulting | Dec, 2021

MMS marketing is a type of mobile advertising that sends enhanced text messages over MMS (Multimedia Messaging Service). Picture messaging is another term for MMS marketing. Because people are more inclined to engage with multimedia content, this marketing strategy has shown to be beneficial to businesses all over the world.Using our Cloud Messaging platform, with eye-catching promotions, vouchers, or special announcements, your company may reach out to thousands of potential customers throughout the world.Create a message that communicates exactly what you want to say to your customers, and deliver it in a way that you know they won’t miss.Instant delivery and creative content: It allows you to send rich content to your audience.See how your campaign is performing in real-time with instan...
Jupyter Notebook into PyCharm. PyCharm is the perfect choice to deploy… | by Jesko Rehberg | May, 2021
ai bot, ai chat, ai chatbot, best chatbot, bots, chatbot, chatbot ai, chatbot app, chatbot online, chatbot website, chatbots, conversation with ai, creating chatbots, jupyter-notebook, pycharm, python, robot chat

Jupyter Notebook into PyCharm. PyCharm is the perfect choice to deploy… | by Jesko Rehberg | May, 2021

PyCharm is the perfect choice to deploy your Jupyter Notebook chatbot as a web app.Photo by Alex Knight on UnsplashMotivation:Jupyter Notebooks are useful for developing on your local machine. But how can other people access your chatbot if it is only alive on your PC? In this post I am going to show you how to go live with your Jupyter Notebook chatbot using PyCharm.Solution:Our Jupyter chatbot’s job is to answer frequently asked questions. For this example, I used the Jupyter Notebook from Parul Pandey. I have only slightly amended that code and logged unanswered user input. Let’s have a look:import randomimport stringfrom sklearn.feature_extraction.text import TfidfVectorizerfrom sklearn.metrics.pairwise import cosine_similarityimport warningswarnings.filterwarnings(‘ignore’)import nltk...