Rattle and R deliver a very sophisticated data mining environment. Data Mining with Rattle is a unique course that instructs with respect to both the concepts of data mining, as well as to the "hands-on" use of a popular, contemporary data mining software tool, "Data Miner," also known as the'Rattle' package in R software. Rattle is a popular GUI-based software tool which'fits on top of' R software. The course focuses on life-cycle issues, processes, and tasks related to supporting a'cradle-to-grave' data mining project. These include: data exploration and visualization; testing data for random variable family characteristics and distributional assumptions; transforming data by scale or by data type; performing cluster analyses; creating, analyzing and interpreting association rules; and creating and evaluating predictive models that may utilize: regression; generalized linear modeling (GLMs); decision trees; recursive partitioning; random forests; boosting; and/or support vector machine (SVM) paradigms. It is both a conceptual and a practical course as it teaches and instructs about data mining, and provides ample demonstrations of conducting data mining tasks using the Rattle R package.

Hands on Real-World Projects on Various Domains of Data Science in Machine Learning, Natural Language Processing, Time Series Analysis Develop Natural Language Processing Models for Customer Sentiments Develop time series forecasting models to predict Prices of stocks Learn how to map your Problem into Data Science problem Learn best practices for real-world data sets. Practical Utility of the learning experience has been well taken care of-which ensures the course to become an interesting one! - Sangita Bhadra Great Job....I Learnt a lot....I recommend this course for anyone reading this.....I will also urge those who have taking any form of introductory course in machine learning....do yourself a favour and get this course....extremely helpful - Adesan Orire Newman Are you looking to land a top-paying job in Data Science? Or are you a seasoned AI practitioner who want to take your career to the next level? Or are you an aspiring data scientist who wants to get Hands-on Data Science and Artificial Intelligence? If the answer is yes to any of these questions, then this course is for you! Data Science is one of the hottest tech fields to be in right now!

Employees are quitting jobs at record rates and companies are having a hard time luring them back. Exacerbating the problem is the fact that employees are now frequently working from home, making it harder for managers to identify employees who are unhappy. Plus, getting new hires up to speed is more challenging when they can't attend in-person training sessions or shadow experienced employees. To solve all these issues, companies are increasingly turning to artificial intelligence. But there's a limit to how much AI can do.

This workshop is the second in a three part series which will focus on exploiting the synergies of the AI and OR communities to transform highly scalable, actionable, automated data-driven decision-making. The goal of this workshop series is to establish a joint strategic vision for AI/OR that will maximize the societal impact of AI and OR in a world that is facing significant challenges due to the COVID-19 pandemic, widening inequalities, and challenges in resilience and sustainability in the food-water-energy nexus, among others. There will be four sessions focusing on foundational elements of trustworthy AI.

In this year's Chatbot Conference, we will explore the latest on Conversational AI, Voice, and Chatbots/Digital Assistants with a strong focus on both how Enterprises are using this technology and how it's becoming implemented in the Metaverse. This promises to be one of our most exciting events, and we are featuring speakers from Google, Salesforce, Microsoft, Charisma, CDI, and more. One of our core topics we will explore is how Brands are starting to use Digital Humans to create experiences in the Metaverse. Imagine that you are watching a great TV Show, like'The Game of Thrones'. Soon, you'll be able to go to The Game Thrones Metaverse, interact with the characters, and open up new stories and plot lines that the TV show can't cover in a 10hr season!

This Asset we are sharing with you the Advanced Reinforcement Learning in Python: cutting-edge DQNs free download links. This is the most complete Advanced Reinforcement Learning course on Udemy. In it, you will learn to implement some of the most powerful Deep Reinforcement Learning algorithms in Python using PyTorch and PyTorch lightning. You will implement from scratch adaptive algorithms that solve control tasks based on experience. You will learn to combine these techniques with Neural Networks and Deep Learning methods to create adaptive Artificial Intelligence agents capable of solving decision-making tasks.

Maps are a great visual tool. We all collect spatial data - holiday destinations, favourite places, areas of interest. But paper maps are limited, and the tools to plot digital maps on a computer can seem daunting. Do you have data that you would like to show on a map but you don't know how to? Or would you like to try a first coding project and want something simple and very visual as a starting project?

TensorFlow can do some amazing things when it comes to computer vision. We just published a full course on the freeCodeCamp.org YouTube channel that will teach you how to use TensorFlow 2 for computer vision applications. Nour Islam Mokhtari created this course. Nour is a Machine Learning Engineer and experienced teacher.

Machine Learning And Data Science With Python Bootcamp 2021 Learn Machine learning and data science with python and solve real world machine learning problems Uplatz offers this in-depth course on Machine Learning concepts and implementing machine learning with Python. Objective: Learning basic concepts of various machine learning methods is primary objective of this course. This course specifically make student able to learn mathematical concepts, and algorithms used in machine learning techniques for solving real world problems and developing new applications based on machine learning. Course Outcomes: After completion of this course, student will be able to: 1. Apply machine learning techniques on real world problem or to develop AI based application 2. Analyze and Implement Regression techniques 3. Solve and Implement solution of Classification problem 4. Understand and implement Unsupervised learning algorithms

Absolutely no previous experience required. Absolutely no previous experience required. Are you aiming for a career in Data Science or Data Analytics? Good news, you don't need a Maths degree - this course is equipping you with the practical knowledge needed to master the necessary statistics. It is very important if you want to become a Data Scientist or a Data Analyst to have a good knowledge in statistics & probability theory.