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A Guide to Analyzing Experimental Data

#artificialintelligence

Have you ever run an experimental study, or performed some A/B testing? If so, you should be familiar with the pre-analysis panic: how can you make the data reveal whether your experiment has worked? Every day -- in economics, public policy, marketing, and business analytics -- we face the challenges that come from running experiments and analyzing what comes out of them. As researchers -- who struggle with a clean and efficient experimental workflow ourselves -- we have decided to share with you a practical guide, complete with all the steps you need to follow when you want to analyze experimental data. We cannot promise that the journey will be short, but we assure you it will be fun!


AIhub monthly digest: July 2021 – ICML, protein folding for all, and AI Song Contest winner announced

AIHub

Welcome to our July 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. In this edition we cover ICML 2021, celebrate award winners, check out new AI reports and strategies, and find out who won the AI Song Contest. This month saw the running of the thirty eighth International Conference on Machine Learning (ICML). There were a huge variety of events, including talks, workshops, tutorial, and socials. We were in (virtual) attendance and managed to catch all of the invited talks.


A Gentle Introduction to Multivariate Calculus

#artificialintelligence

It is often desirable to study functions that depend on many variables. Multivariate calculus provides us with the tools to do so by extending the concepts that we find in calculus, such as the computation of the rate of change, to multiple variables. It plays an essential role in the process of training a neural network, where the gradient is used extensively to update the model parameters. In this tutorial, you will discover a gentle introduction to multivariate calculus. A Gentle Introduction to Multivariate Calculus Photo by Luca Bravo, some rights reserved.


Linear Regression in Python

#artificialintelligence

Forecasting in general means to display, where this exactly is to display or predict future trends using previous or historical data as inputs to obtain an efficient and effective estimation from the predictive data. Forecasting models have different methods for different situations and evaluation procedures are also conducted. Forecasting evaluation includes a procedure to be carried out in step by step that starts with testing of assumptions, testing data and methods, replicating outputs, and accessing outputs. There are three different types of forecasting which basic types of forecasting are: qualitative techniques, time series analysis and projection, and casual models. In this course you will be introduced to Linear Regression in Python, Importing Libraries, Graphical Univariate Analysis, Boxplot, Linear Regression Boxplot, Linear Regression Outliers, Bivariate Analysis, Machine Learning Base Run and Predicting Output.


Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches

#artificialintelligence

COVID-19 is the disease evoked by a new breed of coronavirus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recently, COVID-19 has become a pandemic by infecting more than 152 million people in over 216 countries and territories. The exponential increase in the number of infections has rendered traditional diagnosis techniques inefficient. Therefore, many researchers have developed several intelligent techniques, such as deep learning (DL) and machine learning (ML), which can assist the healthcare sector in providing quick and precise COVID-19 diagnosis. Therefore, this paper provides a comprehensive review of the most recent DL and ML techniques for COVID-19 diagnosis.


Applications of Derivatives

#artificialintelligence

The derivative defines the rate at which one variable changes with respect to another. It is an important concept that comes in extremely useful in many applications: in everyday life, the derivative can tell you at which speed you are driving, or help you predict fluctuations on the stock market; in machine learning, derivatives are important for function optimization. This tutorial will explore different applications of derivatives, starting with the more familiar ones before moving to machine learning. We will be taking a closer look at what the derivatives tell us about the different functions we are studying. In this tutorial, you will discover different applications of derivatives.


VinBrain wins ACM SIGAI Industry Award 2021 for Excellence in Artificial Intelligence

#artificialintelligence

The 2021 ACM SIGAI Industry Award for Excellence in Artificial Intelligence is granted to DrAidTM - the AI-powered Assistant product for Radiologists developed by VinBrain (a subsidiary of Vingroup in Vietnam). This is one of the world's top awards, and only one AI product is selected as the winner each year. The award will be presented at the International Joint Conference on Artificial Intelligence (IJCAI) 2021 from August 19-26, 2021 in Canada. In 2019, the award was granted to Microsoft Corporation. The ACM SIGAI Industry Award for Excellence in Artificial Intelligence (AI) is one of the world's top awards in the field of AI which is given annually to individuals or teams who have transferred original advanced academic research into AI applications.


Chipmaker Ampere to acquire AI startup OnSpecta

ZDNet

Chipmaker Ampere on Wednesday announced its plan to acquire OnSpecta, a startup whose software accelerates AI inference workloads in the cloud and the edge. The terms of the deal were not disclosed. OnSpecta, founded in 2017 and headquartered in Redwood City, Calif, has already collaborated with Ampere. The OnSpecta Deep Learning Software (DLS) has proven to accelerate Ampere-based instances running popular AI-inference workloads by 4x. Last year, Ampere started shipping its Altra processor, an Arm-based server chip for cloud computing and hyperscale data centers.


Mastering JavaScript Essentials 2021 Novice To Professional

#artificialintelligence

Have you always wanted to learn JavaScript but you just don't know where to start? Or maybe you have started to learn Javascript, but you just don't know how to work with basic concepts like the intermediate level JavaScript programming, object-oriented programming in JavaScript, asynchronous programming in JavaScript and JSON objects. If that Sounds Like you…. Then our complete Mastering JavaScript Essentials 2021 Novice to Professional is for You! Join 800,000 Students Who Have Enrolled in our Udemy Courses! Watch the Promo Video to see how you can Get Started Today!


Optimization Algorithm Using Matlab

#artificialintelligence

I'm very glad to have opportunity to teach you one of the most popular and powerful optimization algorithms in this course. If you search FireFly optimization algorithm in google scholar, it could be seen that there are many vast range of papers has been published by implementing this optimization algorithm in different fields of science. In this course, after presenting the mathematical concept of each part of the considered optimization algorithm, I write its code immediately in matlab. All of the written codes are available, however, I strongly suggest to write the codes with me. Notice that, if you don't have matlab or you know another programming language, don't worry at all.