python


AI Most Promising Open Source Projects in 2020

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Are you ready to start your new AI project? In the below map, you'll find a curated list of the most advanced and innovative open source projects to be considered in you data science initiative for 2020. Drop a comment below or submit a pull-request here, if you believe a relevant project was left behind. AllenNLP – An open-source NLP research library, built on PyTorch. Zeppelin – Web-based notebook that enables data-driven, interactive data analytics.


Growth in Machine Learning Leading to Demand for Automated ML - AI Trends

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Machine learning has been used successfully in many disciplines that increasingly depend on it. However, the success relies on human machine learning experts to perform many tasks, according to an account on AutoML.org, a website of the community. These tasks include: Preprocessing and cleaning the data; selecting and constructing appropriate features; selecting an appropriate model family; optimizing model hyper parameters; post-processing machine learning models; and critically analyzing the results. The growth of machine learning applications has created a demand for off-the-shelf machine learning methods that can be used more easily and without necessarily expert knowledge. The goal is to progressively automate these manual tasks in what is being called AutoML.


Machine learning with Python: An introduction

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Machine learning is one of our most important technologies for the future. Self-driving cars, voice-controlled speakers, and face detection software all are built on machine learning technologies and frameworks. As a software developer you may wonder how this will impact your daily work, including the tools and frameworks you should learn. If you're reading this article, my guess is you've already decided to learn more about machine learning. In my previous article, "Machine Learning for Java developers," I introduced Java developers to setting up a machine learning algorithm and developing a simple prediction function in Java.


Machine learning with Python: An introduction

#artificialintelligence

Machine learning is one of our most important technologies for the future. Self-driving cars, voice-controlled speakers, and face detection software all are built on machine learning technologies and frameworks. As a software developer you may wonder how this will impact your daily work, including the tools and frameworks you should learn. If you're reading this article, my guess is you've already decided to learn more about machine learning. In my previous article, "Machine Learning for Java developers," I introduced Java developers to setting up a machine learning algorithm and developing a simple prediction function in Java.


Machine Learning Advanced: Decision Trees in Python

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Free Course - Machine Learning Advanced: Decision Trees in Python [2020] Use Decision Trees to solve business problems and build high accuracy prediction models in Python, Learn how to use decision trees to make predictions for business problems using python. Start with this advanced machine learning tutorial today! Instructor: Start Tes Enroll Now - Machine Learning Advanced: Decision Trees in Python About this Course The course is created on the basis of three pillars of learning: Know (Study) Do (Practice) Review (Self feedback) Know We have created a set of concise and comprehensive videos to teach you all the Excel related skills you will need in your professional career. Add To Cart - GET COUPON CODE Do With each lecture, we have provide a practice sheet to complement the learning in the lecture video. These sheets are carefully designed to further clarify the concepts and help you with implementing the concepts on practical problems faced on-the-job.


Why I Stopped Using Python to Visualise ML Data

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Every Machine Learning engineer must know how to use Facets for their project -- The No Code AI Tool. Facets, a project from Google Research, is being used to visualise datasets, find interesting relationships, and clean them for machine learning. The No Code movement is on the rise and an increasing number of companies expect their engineers to quickly deliver results using pre-existing tools. From building web pages in minutes to creating mobile apps from a simple spreadsheet, no-code does it all. The proponents of building products quickly are pushing hard for the no-code movement precisely because it lets you get to the state of the art in a matter of hours instead of weeks.


6 trends framing the state of AI and ML

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Join Roger Magoulas on March 26 for a live and interactive online session exploring recent O'Reilly AI/ML research. O'Reilly online learning is a trove of information about the trends, topics, and issues tech leaders need to know about to do their jobs. We use it as a data source for our annual platform analysis, and we're using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O'Reilly[1]. Our analysis of ML- and AI-related data from the O'Reilly online learning platform indicates: Get a free trial today and find answers on the fly, or master something new and useful. Engagement with the artificial intelligence topic continues to grow, up 88% in 2018 and 58% in 2019 (see Figure 1), outpacing share growth in the much larger machine learning topic ( 14% in 2018, up 5% in 2019).


Top 7 Machine Learning Frameworks for 2020

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Machine learning is a nightmare without some kind of structure. You can't build everything from scratch, especially if you're in a business setting. Even if you want to (and if you do, comment here and tell us about it!), You need a framework to help bring your vision to life. Here are a few machine learning frameworks designed to help get those projects off the ground.


Complete Python Machine Learning & Data Science for Dummies

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We will discuss about the overview of the course and the contents included in this course. Artificial Intelligence, Machine Learning and Deep Learning Neural Networks are the most used terms now a days in the technology world. Its also the most mis-understood and confused terms too. Artificial Intelligence is a broad spectrum of science which tries to make machines intelligent like humans. Machine Learning and Neural Networks are two subsets that comes under this vast machine learning platform Lets check what's machine learning now.


Machine Learning Books you should read in 2020

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Machine Learning became one of the hottest domain of Computer Science. Each larger company is either applying Machine Learning or thinking about doing so soon to solve their problems and understand their data sets. That means it's time to learn about Machine Learning, especially if you're looking for new Computer Science challenges. A great way to do that is to read a couple of books. If you're just getting started with Machine Learning definitely read this book: Introduction to Machine Learning with Python is a gentle introduction into machine learning.