Instructional Material
Welcome! You are invited to join a meeting: Cleaning up your ROT before migrating to the cloud. After registering, you will receive a confirmation email about joining the meeting.
This webinar will help you understand the benefits and process to create a file inventory: • Cloud vendors are now charging based on storage used, storage is no longer cheap • Successful cloud migrations require planning and file cleanup • Creating a file inventory will help evaluate and choose those files that should be migrated to the cloud • DocAuthority's Data Evolutional Artificial Intelligence (AI) automates the discovery, collection and categorization of documents into well-defined business categories, eliminating reliance on end-user
Social Data Science Semester (SDS)
This module is a condensed introduction to the "Data Science Pipeline", taking students from data acquisition over pre-processing and modelling to evaluation and presentation. This module will focus on unstructured network data. Students will learn how to explore and analyse natural language (text) as well as relational (network) data of various kinds. This module focuses on the most recent developments in machine learning, which are deep learning and artificial intelligence (AI) applications, to analytics and particularly useful in Big Data settings. The module will provide a solid foundation to this exciting and rapidly developing field, and enable the students to on-demand update and acquire new knowledge.
Social Data Science Semester (SDS)
This module is a condensed introduction to the "Data Science Pipeline", taking students from data acquisition over pre-processing and modelling to evaluation and presentation. This module will focus on unstructured network data. Students will learn how to explore and analyse natural language (text) as well as relational (network) data of various kinds. This module focuses on the most recent developments in machine learning, which are deep learning and artificial intelligence (AI) applications, to analytics and particularly useful in Big Data settings. The module will provide a solid foundation to this exciting and rapidly developing field, and enable the students to on-demand update and acquire new knowledge.
Practical AI #65: Intelligent systems and knowledge graphs with James Fletcher, principal scientist at Grakn Labs
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mbadry1/DeepLearning.ai-Summary
This repository contains my personal notes and summaries on DeepLearning.ai I've enjoyed every little bit of the course hope you enjoy my notes too. This is by far the best course series on deep learning that I've taken. If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech.
Chatbot B2B Case Study: Reduce Call Volume, Improve Customer Experience
Chatbots for B2B are a very hot topic, but so far there are few live examples to share. In this pacesetter case study, see a successful B2B chatbot in action. Like many organizations, TSIA member Citrix, a leader in employee productivity tools, was challenged with increasing call deflection while simultaneously improving customer experience. With their customers ranging from small privately owned businesses to large enterprise organizations, they needed a solution that would meet the specific needs of each buyer. While this appeared to be an impossible feat, Citrix was able to accomplish this goal by implementing Bold360, LogMeIn's AI chatbot and live-agent software.
Data Integration Life Cycle Management with SSIS - Programmer Books
Build a custom BimlExpress framework that generates dozens of SQL Server Integration Services (SSIS) packages in minutes. Use this framework to execute related SSIS packages in a single command. You will learn to configure SSIS catalog projects, manage catalog deployments, and monitor SSIS catalog execution and history. Data Integration Life Cycle Management with SSISÂ shows you how to bring DevOps benefits to SSIS integration projects. Practices in this book enable faster time to market, higher quality of code, and repeatable automation.
Artificial Intelligence, Machine Learning and Python Analytics Insight
Ever since computers were invented, there has been an exponential growth in their ability and potential to perform various tasks. In order to use computers across diverse working domains, humans have developed computer systems while increasing their speed, and reducing size with respect to time. Artificial Intelligence pursues the stream of developing the computers or machines to be as intelligent as humans themselves. In this article we will scrape the top layer about the concepts of artificial intelligence that will help understand related concepts like Artificial Neural Networks, Natural Language Processing, Machine Learning, Deep Learning, Genetic algorithms etc. Along with this, we will also learn about its implementation in Python.