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Featured Blog Posts – May 2019 Archive (99)

Profiling Store Visitors

Our Telecom Client was developing a Big Data Product that will profile demography (Age, Gender, Income, Ethnicity, Marital Status) of the visitors of the stores receiving feed from the wi-fi routers placed in the stores. Client used to receive daily feed of router data in its server which were then uploaded in HDFS / Hive Tables in the data lake for analysis.

Maintaining data quality was a serious issue without which the reports would have been erroneous. A daily e-mail used to get…

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Added by Dr. Moloy De on May 23, 2019 at 9:29pm — No Comments

How to Install and Run Hadoop on Windows for Beginners

Introduction

Hadoop is a software framework from Apache Software Foundation that is used to store and process Big Data. It has two main components; Hadoop Distributed File System (HDFS), its storage system and MapReduce, is its data processing framework. Hadoop has the capability to manage large datasets by distributing the dataset into smaller chunks across multiple machines and performing parallel computation on it…

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Added by Divya Singh on May 23, 2019 at 8:30pm — No Comments

Upcoming Book: Foundations of Data science

Not to be confused with this free Microsoft book with same title.

Data science underlies Amazon's product recommender, LinkedIn's People You Know feature, Pandora's personalized radio stations, Stripe's fraud detectors, and the incredible insights arising from the world's increasingly ubiquitous sensors. In the future,…

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Added by Capri Granville on May 23, 2019 at 9:00am — No Comments

Free Book: Statistics, Dataviz, and Data Cleaning with R

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…

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Added by Capri Granville on May 23, 2019 at 9:00am — No Comments

Free Book: Foundations of Data Science (from Microsoft Research Lab)

By Avrim Blum, John Hopcroft, and Ravindran Kannan (2018). 

Computer science as an academic discipline began in the 1960s. Emphasis was on programming languages, compilers, operating systems, and the mathematical theory that supported these areas. Courses in theoretical computer science covered finite automata, regular expressions, context-free languages, and computability. In the 1970s, the study of algorithms was added as an important component of…

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Added by Capri Granville on May 23, 2019 at 9:00am — 1 Comment

Three Books About the Mathematics of Data

There are plenty of resources on the Internet to learn linear algebra or to get a refresher, including our own tutorial (here). Below are three interesting books found on Amazon. …

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Added by Capri Granville on May 23, 2019 at 9:00am — 1 Comment

Lecture Notes by Andrew Ng : Full Set

The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester. The topics covered are shown below, although for a more detailed summary see lecture 19. The only content not covered here…

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Added by Capri Granville on May 23, 2019 at 9:00am — No Comments

Free Textbook: Probability Course, Harvard University (Based on R)

A free online version of the second edition of the book based on Stat 110, Introduction to Probability by Joe Blitzstein and Jessica Hwang, is now available here. Print copies are available via CRC Press, Amazon, and…

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Added by Capri Granville on May 23, 2019 at 8:30am — 1 Comment

Google Machine Learning Glossary

This glossary defines general machine learning terms as well as terms specific to TensorFlow. Below is a small selection of the most popular entries. You can access this glossary here. For other related glossaries, follow this link.

  • A/B testing
  • activation…
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Added by Capri Granville on May 23, 2019 at 8:30am — No Comments

Deep Knowledge: Next Step After Deep Learning

This article was written by David March.

 Data science has been around since mankind first did experiments and recorded data. It is only since the advent of big and heterogenous data that…

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Added by Andrea Manero-Bastin on May 23, 2019 at 4:30am — No Comments

What is Data Lake and How to Improve Data Lake Quality

Introduction

Building data pipelines is a core component of data science at a startup. In order to build data products, you need to be able to collect data points from millions of users and process the results in near real-time. Today, many organizations nowadays are struggling with the quality of their data. Data quality (DQ) problems can arise in various ways. Here are common causes of bad data quality:

  • Multiple data sources:…
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Added by Divya Singh on May 22, 2019 at 9:00pm — No Comments

Price Forecasting: Applying Machine Learning Approaches to Electricity, Flights, Hotels, Real Estate, and Stock Pricing

When you give customers advice that can help them save some money, they will pay you back with loyalty, which is priceless. Interesting fact: Fareboom users started spending twice as much time per session within a month of the release of an airfare price forecasting feature. This tool continues to grow conversion for our partner.

Besides travel, price predictions find their application in various scenarios. Commodity traders, investors, construction developers, or energy generators…

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Added by Kateryna Lytvynova on May 22, 2019 at 7:30am — No Comments

An Introduction to Python Virtual Environment

Data Science, Machine Learning, Deep Learning, and Artificial Intelligence are some of the most heard about buzzwords in the modern analytical eco-space. The exponential growth of technology in this regard has simplified our lives and made us more machine dependent. The astonishing hype surrounding such technologies has prompted professionals from various disciples to hop on to the ship and consider analytics as their career option.

To master Data Science or Artificial Intelligence in…

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Added by Divya Singh on May 21, 2019 at 9:30pm — No Comments

29 Statistical Concepts Explained in Simple English - Part 13

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…

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Added by Vincent Granville on May 21, 2019 at 5:30pm — No Comments

Implementing Knowledge Graphs in Enterprises - Some Tips and Trends

Tips

  1. Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for…
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Added by Andreas Blumauer on May 21, 2019 at 5:33am — No Comments

Artificial Intelligence Is Spurring Innovation In The Field Of Education!

Artificial Intelligence is spreading its wings almost everywhere. Starting from the businesses to even the agricultural fields, AI is powering the world in many ways than one. There have been various discussions surrounding the fact that AI has the potential to impact the education sector as well. There seems to be various possibilities that Artificial Intelligence is expected to spur innovation in the field of education. Starting from becoming a latest form of…

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Added by Samual Alister on May 21, 2019 at 5:10am — No Comments

Successful Augmented Analytics Initiatives Do Not End with Implementation!

The successful implementation of an augmented analytics solution for business users is not just about choosing a cost-effective tool and completing a timely deployment, nor does the process stop with training. In order to get business users to embrace and adopt self-serve augmented data discovery tools, the enterprise must approach the implementation with appropriate change management processes.

If you want a business user or a team to align with the Citizen Data…

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Added by Kartik Patel on May 21, 2019 at 1:30am — No Comments

Prediction of Customer Churn with Machine Learning

Machine Learning is the word of the mouth for everyone involved in the analytics world. Gone are those days of the traditional manual approach of taking key business decisions. Machine Learning is the future and is here to stay.

However, the term Machine Learning is not a new one. It was there since the advent of computers but has grown tremendously in the last decade due to the massive amounts of data that’s getting generated, and the enormous computational power that modern-day…

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Added by Divya Singh on May 20, 2019 at 10:30pm — No Comments

Deep Learning Explainability: Hints from Physics


Nowadays, artificial intelligence is present in almost every part of our lives. Smartphones, social media feeds, recommendation engines, online ad networks, and navigation tools are some…

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Added by Marco Tavora on May 20, 2019 at 11:46am — No Comments

Should You Be Recommending Deep Learning Solutions in Your Company?

Summary:  If you are guiding your company’s digital journey, to what extent should you be advising them to adopt deep learning AI methods versus traditional and mature machine learning techniques.

 

By now everyone is at least familiar with using AI/ML as a required cornerstone of company strategy.  Frequently…

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Added by William Vorhies on May 20, 2019 at 8:33am — 1 Comment

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