A myriad of options exist for classification. In general, there isn't a single "best" option for every situation. That said, three popular classification methods— Decision Trees, k-NN & Naive Bayes—can be tweaked for practically every situation.
Naive Bayes and K-NN, are both examples of supervised learning (where the…Continue
Added by Stephanie Glen on June 19, 2019 at 6:49am — No Comments
The lifecycle of data travels through six phases:
The lifecycle "wheel" isn't set in stone. While it's common to move through the phases in order, it's possible to move in either direction (i.e. forward, backward) at any stage in the cycle. Work can also happen in several phases at the same time, or you can skip over…Continue
Can design sprints work for Artificial Intelligence applications?
Last week, for the first time, I attended a meetup on Design Sprints( The Design Sprint Underground)
I had heard of Design sprints from Google – but I am not an expert. The organiser, Eran, created…Continue
Summary: Forrester has just released its “New Wave™: Automation-Focused Machine Learning Solutions, Q2 2019” report on leading stand-alone automated machine learning platforms. This is our first good side-by-side comparison. You might also want to consider some who were not included.
Added by William Vorhies on June 17, 2019 at 8:30am — 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 June 15, 2019 at 2:00pm — No Comments
This post is a part of my forthcoming book on Mathematical foundations of Data Science.
In this post, we use the Perceptron algorithm to bridge the gap between high school maths and deep learning. Welcome comments
As part of my role as course director of the Artificial Intelligence: Cloud and Edge Computing at the University of…Continue
Added by ajit jaokar on June 14, 2019 at 12:33pm — No Comments
I stumbled upon this book by chance, when searching for material about time series (probably the most interesting chapter in this collection.) The various chapters are accessible from the top tabs, on this web page. It is mostly about R, but it has a few interesting chapters on statistical science too. Below is a…Continue
Added by Capri Granville on May 23, 2019 at 9:00am — No Comments
This article is based on Unsupervised Learning algorithm: Hierarchical Clustering. This is the brief illustration with a practical working example of forming unsupervised hierarchical clusters and testing them to assure that you have formed the right clusters. This is a real-life data world example which can be studied and evaluated as data is provided for personal use and practice. There are variations to each topic in data science but there is a brief basic pattern…Continue
Added by Neeraj on June 13, 2019 at 8:36am — No Comments
After decades of a heavy slog with no promise of success, quantum computing is suddenly buzzing! Nearly two years ago, IBM made a quantum computer available to the world. The 5-quantum-bit (qubit) resource they now call the IBM Q experience. It was more like a toy for researchers than a way of getting any serious number crunching done. But 70,000 users worldwide have registered for it, and the qubit count in this…Continue
Added by Divya Singh on June 13, 2019 at 8:00pm — No Comments
The only way of surviving in the market is to continuously transform from an older strategy to a new strategy. It is this transformation that leads the company to another level and can be called an innovative company. Technology has manifested to be the most innovative part of the…Continue
Added by Smith Johnson on June 14, 2019 at 2:26am — No Comments
Added by Stephanie Glen on June 15, 2019 at 7:53am — No Comments
By Ajit Jaokar and Dan Howarth. With contributions from Ayse Mutlu.
Exclusively for Data Science Central members, with free access. You can download this book (PDF) here.
This tutorial began as a series of weekend workshops created by Ajit Jaokar and Dan Howarth. The idea was to work with a specific (longish) program such that we explore as much of it…Continue
Added by Vincent Granville on May 16, 2019 at 8:30am — No Comments
The internet is evolving day by day, and when users shop online, they are flooded with thousands of results, leaving them in a dilemma to choose the best possible product that suits their requirements. Have you ever thought of how Google Ads precisely knew what you need and display…Continue
Added by Guido van Capelleveen on June 13, 2019 at 2:44am — No Comments
Do you know that the global business community will be spending $310 billion on the Internet of Things (IoT) by 2020?
Isn’t it a huge investment! Why is this trend booming?
Actually, the IoT has encapsulated devices. The software, sensors, actuators and connectivity through vehicles and home appliances are penetrating deeply. This networking model is skyrocketing in almost every walk of life. That’s why small entrepreneurs to big industrialists are hungry…Continue
Added by Moses Vandenberg on June 13, 2019 at 5:30am — No Comments
Innovation and advancement mean subtracting the obvious things and adding meaningful things. Technology is successfully on this path and is doing wonders. It is very obvious in this era that technology is winning the race in innovation and advancement and has exceeded the humanity. The sectors and trends that are pushing…
Added by Smith Johnson on June 12, 2019 at 2:49am — No Comments
Our client was an Emergency Response Management organization who handles medical, police and fire emergencies through the " 1-0-8 Emergency service". Currently the organization runs around 690 ambulances. An analysis is run on historic data extracted from client's management database. The live data input is fed to a simulation model to propose an optimal ambulance allocation providing an opportunity of cost reduction for the organization.
In probability theory and statistics, the…Continue
Added by Dr. Moloy De on June 12, 2019 at 6:51am — No Comments
Dramatically improving currency trading models with AI using Keras Deep Learning and PivotBillions.…
Added by Benjamin Waxer on June 12, 2019 at 1:25am — No Comments
Logistic regression is typically used when the response Y is a probability or a binary value (0 or 1). For instance, the chance for an email message to be spam, based on a number of features such as suspicious keywords or IP address. In matrix notation, the model can be written as
where X is the observations matrix,…Continue
Added by Vincent Granville on June 12, 2019 at 9:00am — No Comments
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…Continue
Added by Vincent Granville on June 11, 2019 at 3:00pm — No Comments
P-values are used in statistics and scientific publications, much less so in machine learning applications where re-sampling techniques are favored and easy to implement today thanks to modern computing power. In some sense, p-values are a relic from old times, when computing power was limited and mathematical / theoretical formulas were favored and easier to deal with than lengthy computations.
Recently, p-values have been criticized and even banned by some…Continue
Added by Vincent Granville on June 11, 2019 at 7:30am — No Comments