The gaming industry is on its rise nowadays. With more than 2 billion players all over the world gaming industry is a resource of enormous revenues and…

Introduction to topic model:

In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body. 

In topic modeling, a topic is defined by a cluster of words with each word in the cluster having a probability of occurrence for the given topic, …

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.  

Featured Resources and Technical…

Interaction plots are used to understand the behavior of one variable depends on the value of another variable. Interaction effects are analyzed in regression analysis, DOE (Design of Experiments) and ANOVA (Analysis of variance).

This blog will help you to understand the interaction plots and its effects, how to interpret them in statistical designs, and the problems you will face if you don't include them in your statistical models. In any statistical study, whether it's a product…

Background

One of the hardest problem in AI is not technical

It is social

Specifically, it is the problem of “educating people for living and working in a world dominated by AI”

This blog is based on my talk and notes in panels at the…

Key points of this blog include:

• Digital Transformation sweeps aside traditional industry borders to create new sources of customer and operational value
• Unfortunately, Digital Transformation and “smart” initiatives are struggling, and organizations will need a more pragmatic approach to successful execution per Forrester research
• Organizations must define their “smart” initiatives from perspective of stakeholder…

Kafka monitoring is an important and widespread operation which is used for the optimization of the Kafka deployment. This process may be smooth and efficient for you by applying one of the existing monitoring solutions instead of building your own. Let’s say, we use solution with Apache Kafka for message transfer and…

A recent visit to a local hospital provided some insight on a particular problem in health care. After speaking to a few healthcare professionals, it was revealed that patients who have surgery are at a significantly higher risk at developing a Pulmonary Embolism (PE) as a result of a Deep Vein Thrombosis (DVT) or blood clot. Clots are also referred to as a thrombus. However, once a clot begins to travel it is called…

Here is our selection of featured articles, news, and resources posted since Monday:

Resources:

• Choosing from Popular Python Web Frameworks 
• How do I learn AI using Python? …

This article was written by Datapred.

In a previous post, we explained the concept of cross-validation for time series, aka backtesting, and why proper backtests matter for time series modeling.

The goal here is to dig deeper and discuss a few coding tips that will help you cross-validate your predictive models correctly.…

Businesses need to effectively manage and plan their day-to-day activities, business strategies and future planning. To efficiently collect and manage all such…

With increased digitization comes the need for infrastructural stability and safety. That’s where TensorFlow can provide maximum returns, especially in the road safety domain. On-road traffic accidents can be minimized with greater efficiencies in overall traffic management. There is also greater control and oversight when dealing with multiple vehicles across various roads.…

Ensemble methods take several machine learning techniques and combine them into one predictive model. It is a two step process: 

1. Generate the Base Learners: Choose any combination of base learners, based on accuracy and diversity. Each base learner can produce more than one predictive model, if you change variables such as case weights, guidance parameters, or input space partitions.
2. Combine Estimates from the Base…

This article delves in some of the widespread Python web frameworks and what makes them popular today.

Python is one of the most popular and versatile programming languages. There are thousands of Python packages, and these allow you to extend Python capabilities to any domain,be it web development, Internet of Things (IoT), artificial intelligence, or machine learning, and scientific computing. We can work with many different web frameworks and packages to…

"We are in a brave new world where not only do our children talk back to us, but so do our appliances."  – Mohammed Dastagir

Smart machines to make this world a smart planet was advocated nearly 70 years ago by Alan Turing.  In his 1950 article "Computing Machinery and Intelligence" he has stated as…

SVMs (Support Vector Machines) are a way to classify data by finding the optimal plane or hyperplane that separates the data. In 2D, the separation is a plane; In higher dimensions, it's a hyperplane. For simplicity, the following picture shows how SVM works for a two-dimensional set.

Click on picture to zoom…

Summary:  Whether you’re a data scientist building an implementation case to present to executives or a non-data scientist leader trying to figure this out there’s a need for a much broader framework of strategic thinking around how to capture the value of AI/ML.

There are many articles written from a tools…

Machine Learning (ML) has been among the top strategies for almost every organization - whoever adopts the new methodology early and quickly establishes the corporate capability will gain competitive advantages in the market. 

However, because ML is still a relatively new field and data science is a skillset that is scarce for many companies, how to make the journey move at optimal speed without disaster or time wasted…