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iiot machinelearning_2022-05-20_04-17-50.xlsx

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The graph represents a network of 1,175 Twitter users whose tweets in the requested range contained "iiot machinelearning", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 20 May 2022 at 11:21 UTC. The requested start date was Friday, 20 May 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 16-hour, 1-minute period from Tuesday, 17 May 2022 at 07:58 UTC to Friday, 20 May 2022 at 00:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


Feature Selection For Machine Learning - AI Summary

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Free Coupon Discount – Feature Selection for Machine Learning, From beginner to advanced Throughout this course you will learn a variety of techniques used worldwide for variable selection, gathered from data competition websites and white papers, blogs and forums, and from the instructor's experience as a Data Scientist. This course is therefore suitable for complete beginners in data science looking to learn how to go about to select features from a data set, as well as for intermediate and even advanced data scientists seeking to level up their skills. Throughout this course you will learn a variety of techniques used worldwide for variable selection, gathered from data competition websites and white papers, blogs and forums, and from the instructor's experience as a Data Scientist. This course is therefore suitable for complete beginners in data science looking to learn how to go about to select features from a data set, as well as for intermediate and even advanced data scientists seeking to level up their skills.


CS229: Machine Learning - AI Summary

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CS229: Machine Learning Course Description This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing. Course Description This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control.


Create Machine Learning Models in Microsoft Azure

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Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production.


Advanced Data Science with IBM

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Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models. In this course we teach you the fundamentals of Apache Spark using python and pyspark. We'll introduce Apache Spark in the first two weeks and learn how to apply it to compute basic exploratory and data pre-processing tasks in the last two weeks.


Teach yourself data science at your own pace for less than $40

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The following content is brought to you by ZDNet partners. If you buy a product featured here, we may earn an affiliate commission or other compensation. Artificial intelligence (AI) has become so commonplace that it's easy to forget it was once a science fiction pipe dream. But AI and the machine learning concepts behind it are still new enough that programmers and data scientists will be in demand for the foreseeable future. So if you want to pursue a career in one of the fields where data science know-how is essential, this e-learning bundle can serve as a great first step.


Advanced Reinforcement Learning: policy gradient methods

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Sample efficiency for policy gradient methods is pretty poor. We throw out each batch of data immediately after just one gradient step. This is the most complete Reinforcement Learning course series 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.


Complete Machine Learning with R Studio - ML for 2022

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You're looking for a complete Machine Learning course that can help you launch a flourishing career in the field of Data Science & Machine Learning, right? You've found the right Machine Learning course!


Create a Drum Machine with Python and Pygame

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A drum machine is a fun project to create to practice your Python skills. We just published a full course on the freeCodeCamp.org YouTube channel that will teach you how to create a drum machine project using Python and Pygame. Pete LeMaster created this course. Pete has created a bunch


GitHub - kandarpkakkad/Machine-Learning-A-to-Z: Machine Learning A-Z (Udemy)

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The objective of this course is to learn Machine Learning concepts and be handy with coding of machine learning. Here I have the solutions and codes of "Machine Learning A to Z" course of Udemy.