Data Science and Machine Learning are furtive, they go un-noticed but are present in all ways possible and everywhere. They contribute significantly in all the fields they are applied and leave us with evidence which we can rely on and take data-driven directions. Today, a very interesting area we are going to see an example of Data Science and Machine Learning is ‘Crimes’. We are going to focus on types of crimes taken place across…Continue
Added by Neeraj on July 25, 2019 at 7:30am — No Comments
Building accurate models takes a great deal of time, resources, and technical ability. The biggest challenge? You almost never know what model or feature combination will end…
Added by Benjamin Waxer on July 25, 2019 at 4:12am — No Comments
In my previous posts, I compared model evaluation techniques using Statistical Tools & Tests and commonly used Classification and Clustering evaluation techniques
In this post, I'll take a look at how you can compare regression models. Comparing…Continue
Added by Stephanie Glen on July 24, 2019 at 3:00pm — No Comments
IoT (Internet of Things) has not quite taken off yet as envisaged - Will the cloud overcome the shortcomings of IoT? I believe that the Cloud is the missing link that enables IoT to create a critical mass towards deployment.
The vision outlined here is part of my forthcoming book on Data Science…Continue
Logistic Regression is a statistical approach which is used for the classification problems. In statistics, the logistic model (or logit model) is used to model the probability of a certain class or event existing such as pass/fail, win/lose, alive/dead or healthy/sick. This can be combined to model several classes of events such as determining whether an image contains a cat, dog, lion, etc… Each object is detected in the image would be assigned a probability between 0 and 1 and the sum…Continue
Added by Suresh on July 23, 2019 at 5:30am — No Comments
Knowing when and how to choose the right statistical hypothesis test is no mean feat. It can takes years of learning and practice before you get comfortable with it.
Fortunately, there are ways to shortcut this by having a process, a strategy and a nice, big diagram!
Here I'm going to give you all three!
Added by Lee Baker on July 23, 2019 at 3:30am — No Comments
Summary: Python’s open-source and high-level nature, as well as its comprehensive libraries, make it the perfect fit to solve the numerous real-life ML challenges.
The increasing popularity and accessibility of Artificial Intelligence solutions is rapidly reshaping many industries, from healthcare through finance to aviation. Although the application of the latest technologies has always been an essential consideration for companies striving to get…Continue
Added by Łukasz Grzybowski on July 23, 2019 at 1:30am — No Comments
Added by Lewis Wynne-Jones on July 22, 2019 at 8:00am — No Comments
Summary: Artificial General Intelligence (AGI) is still a ways off in the future but surprisingly there’s been very little conversation about how to measure if we’re getting close. This article reviews a proposal to benchmark existing AIs against animal capabilities in an Animal-AI Olympics. It’s a real thing and just now accepting entrants.
Added by William Vorhies on July 22, 2019 at 7:33am — No Comments
Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential. The key, however, lies with understanding data and its insights.
Logistics, like other domains, can also leverage from the several advantages of data. It all begins with what to do with the collected data. Data Science will come into the picture with its amalgamation of statistical &…Continue
Added by Bhushan Patil on July 21, 2019 at 8:37pm — No Comments
In part 1, I compared a few model evaluation techniques that fall under the umbrella of 'general statistical tools and tests'. Here in Part 2 I compare three of the more popular model evaluation techniques for classification and clustering: confusion matrix, gain and…Continue
Added by Stephanie Glen on July 21, 2019 at 9:30am — No Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.
Added by Vincent Granville on July 21, 2019 at 8:00am — No Comments
Excel is often poorly regarded as a platform for regression analysis. The regression add-in in its Analysis Toolpak has not changed since it was introduced in 1995, and it was a flawed design even back then. (See this link for a discussion.) That’s unfortunate, because an Excel file can be a very good place in which to build regression models, compare and refine them, create…Continue
This article was written by Louis Tiao.
In this series of notebooks, we demonstrate some useful patterns and recipes for visualizing animating optimization algorithms using Matplotlib.
Added by Andrea Manero-Bastin on July 19, 2019 at 10:30pm — No Comments
One of my most memorable experiences during my college years was having an English professor who spoke entirely in complete sentences.There were no spoken sentence fragments, dangling thoughts or misuse of adjectives, verbs or nouns. When I first met him, I was stunned at his level of commitment to this principle. I often wondered how challenging this must be for him and whether or not the…Continue
Added by Richard Charles, PhD on July 19, 2019 at 6:00pm — No Comments
Before I kick off this new blog, I’m happy to announce the release of my 3rd book” "The Art of Thinking Like A Data Scientist”. This book is designed to be a workbook – a pragmatic tool that you can use to help your organization leverage data and analytics to power your business and operational models. The book is jammed with templates, worksheets, examples and…Continue
Added by Bill Schmarzo on July 19, 2019 at 12:58pm — No Comments
Ecommerce sites generate tons of web server log data which can provide valuable insights through analysis. For example, if we know which users are more likely to buy a product, we can perform targeted marketing, improve relevant product placement on our site and lift conversion rates. However, raw web logs are often enormous and messy so preparing the data to train a predictive model is time consuming for data scientists.…
Added by Ayumi Owada on July 18, 2019 at 2:00pm — No Comments
A neural network is a series of algorithms that aims to identify underlying relationships in a set of data through a process that is similar to the way the human brain functions.
Keras is an open-source library written in Python for advancing and evaluating deep learning models. It enables you to define and train neural network models in a few lines of code. In this post, we will learn how to build a neural network using…Continue
Added by Packt Publishing on July 18, 2019 at 3:00am — No Comments
I found an interesting, free book which is still a work in progress book – The Data Engineering Cookbook
I will be contributing through the author (Andreas Kretz.com) patreon site : (…Continue
Added by ajit jaokar on July 17, 2019 at 11:00am — No Comments
Those of us who were data science practitioners before the ubiquity of buzz words like “Fourth Industrial Revolution”, remember a time when data science was being described as “utter hubris” by some of the worlds leading quants. All these buzz words, coupled with misplaced applications of data science have turned it into a fairly nebulous concept. Which is a problem.
In facilitating my data science workshops I've realized there are two main groups of audiences and learners.…