Multi-layered network exploration (MuLaNE) problem is an important problem abstracted from many applications. In MuLaNE, there are multiple network layers where each node has an importance weight and each layer is explored by a random walk. The MuLaNE task is to allocate total random walk budget $B$ into each network layer so that the total weights of the unique nodes visited by random walks are maximized. We systematically study this problem from offline optimization to online learning. For the offline optimization setting where the network structure and node weights are known, we provide greedy based constant-ratio approximation algorithms for overlapping networks, and greedy or dynamic-programming based optimal solutions for non-overlapping networks. For the online learning setting, neither the network structure nor the node weights are known initially. We adapt the combinatorial multi-armed bandit framework and design algorithms to learn random walk related parameters and node weights while optimizing the budget allocation in multiple rounds, and prove that they achieve logarithmic regret bounds. Finally, we conduct experiments on a real-world social network dataset to validate our theoretical results.

Welcome to the first course in Term 1 as part of the series "MBA in Artificial Intelligence Digital Marketing". This game-changing course in 2021 will cover artificial intelligence tools in content creation, curation, augmented reality, and digital marketing and will take you on a glimpse into the future. We will also look at influencer marketing tools, content trends and a bit of competitor analysis through the use of BuzzSumo. Why learn this amazing artificial intelligence course and how is this a differentiator for content creators? This course can change your life if you are a content expert.

The creation of this course "Python Programming Tutorial For The Absolute Beginner Code" has been for me an exciting personal journey in discovering how Python can be used today for procedural and object oriented programming, to develop applications and to provide online functionality. Example code listed in this course "Python Programming Tutorial For The Absolute Beginner Code" describes how to produce Python programs. I sincerely hope you enjoy discovering the exciting possibilities of Python, and have as much fun with it as I did in recording this course. To get the most out of this course and have an amazing Python Programming journey, I invite you to take the lectures one by one and carefully watch me writing code examples, then please learn the specific concept exposed in the lecture by coding your self using the attached PDF file which contains specifically the word "instruction"; for example if you take the lecture "Writing lists" then use the attached PDF called "Writing lists instruction" to code yourself and learn how to write and manipulate lists in Python. Learning Python programming from scratch isn't easy, but not at all hard if you start your learning journey with the best python programming course.

Welcome to the first course in Term 2 as part of the series "MBA in Artificial Intelligence Digital Marketing". Artificial Intelligence (AI) seems to be a unique technology of making a machine, a robot fully autonomous. AI is an analysis of how the machine is thinking, studying, determining, and functioning when it is trying to solve problems. These kinds of problems are present in all fields, the most emerging ones, and even beyond. The aim of Artificial Intelligence is to enhance machine functions relating to human knowledge, such as reasoning, learning, and problems along with the ability to manipulate things.

ISRO has invited applications from interested candidates for a free online course called "Machine learning to Deep Learning: A journey for remote sensing data classification". The short course can be completed in five days, and participants will also receive a certificate. The course will be conducted through the Indian Institute of Remote Sensing (IIRS) as part of its outreach program. The program coordinator is Dr. Poonam S Tiwari who is from the IIRS DLP team. The ISRO free online course will be conducted from 5 to 9 July in the evening from 4 to 5:30 PM.

Then this course is for you! This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. Enroll Now - Machine Learning A-Z: Hands-On Python & R In Data Science Students also bought Artificial Intelligence A-Z: Learn How To Build An AI Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!

Karuna Maheshwari is Master in Arts and Commerce background. His Field of Interest is Audit, Business Economics and E-Commerce. In the Education she also Hold the Degree in Post Graduate Diploma in the Computer. She has 15 Years of Teaching Experience. She has the Commanding Knowledge in the Field of Economics and History.

I am a self taught software engineer focusing on software development and machine learning. I focus on teaching my students practical software engineering so they can perform at their best abilities in the real world. I also have experience with artificial intelligence and machine learning.

With the increased adoption of E-learning platforms, keeping online learners engaged throughout a lesson is challenging. One approach to tackle this challenge is to probe learn-ers periodically by asking questions. The paper presents an approach to generate questions from a given video lecture automatically. The generated questions are aimed to evaluate learners' lower-level cognitive abilities. The approach automatically extracts text from video lectures to generates wh-kinds of questions. When learners respond with an answer, the proposed approach further evaluates the response and provides feedback. Besides enhancing learner's engagement, this approach's main benefits are that it frees instructors from design-ing questions to check the comprehension of a topic. Thus, instructors can spend this time productively on other activities.

At each step, get practical experience by applying your skills to code exercises and projects. This program is intended for students with experience in Python, who have not yet studied Machine Learning topics.