Andrés Hirane

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Distributed architecture concepts I learned while building a large payments system

I joined Uber two years ago as a mobile software engineer with some backend experience. I ended up building the payments functionality in the app - …

Software Development

Introducing TensorFlow Hub: A Library for Reusable Machine Learning Modules in TensorFlow

<i>Posted by</i> <i>Josh Gordon</i><i>, Developer Advocate for TensorFlow</i><p>One of the things that’s so fundamental in software development that it’s easy to overlook is …

Machine Learning

10 Machine Learning Algorithms You Should Know to Become a Data Scientist

Machine learning practitioners have different personalities. While some of them are “I am an expert in X and X can train on any type of data,” where …

Cross Validated

Time series forecasting in r : ts() function in forecast package

I am currently working on a sample data that requires me to perform time series forecasting in R on a given set of data.So i need to forecast for …

Data Science

[D] To PhD or not to PhD ?

Are PhDs really required to work in an AI lab?I have a French engineering degree (equivalent to an MSc), majored in datascience and robotics, and an …

Data Science

Writing a Resume for a Data Science Career

Source: PexelsSo, you’ve decided to move onto the next stage of your data science career, whether you’re just starting out or believe you’re ready to …

Data Science

Facebook vs. Cambridge Analytic Shows Data Science’s Increasingly Complex Social Impact

Opinion<p>Posted: Mar 24, 2018 12:01 AM<p><i>The opinions expressed by columnists are their own and do not represent the views of Townhall.com.</i><p>Data science …

Big Data

Introducing Distributed Data Vending, A Compliant Way to Share Sensitive Data

The advent of blockchain infrastructures paves the way for a new domain of data vending, allowing individual data owners to directly benefit from …

Blockchain

The Ultimate Guide To Speech Recognition With Python

Have you ever wondered how to add speech recognition to your Python project? If so, then keep reading! It’s easier than you might think.<p>Far from a …

Python Programming

How Leadership Can Create A Data-Driven Culture And New Careers In The Future Workplace

Why am I writing about “big data?” The answer is simple: Big data isn’t huge — it’s <i>massive</i>. By 2020, the digital universe will grow to hold 44 trillion gigabytes of data, a result of data amounts more than doubling every two years. As information from digital platforms such as wireless sensors, …

Leadership

Stop Feeding Garbage To Your Model! — The 6 biggest mistakes with datasets and how to avoid them.

Learn how to build killer datasets by avoiding the most frequent mistakes in Data Science, plus tips, tricks and kittens.<p>Introduction<p>If you haven’t …

Data Science

MoMA: Modern Multivariate Analysis in R

Background<p>Multivariate analysis -- the study of finding meaningful patterns in datasets -- is a key technique in any data scientist's toolbox. Beyond …

Black-box optimization — Graduate Descent

Black-box optimization algorithms are a fantastic tool that everyone should be aware of. I frequently use black-box optimization algorithms for …

Why building the right data science team for your business is crucial

<i>Algorithms don't change the business, only teams that understand the business outcomes with data will be able to scale up, experts say.</i>According to …

Artificial Intelligence

Minimum Cost Path Analysis (Python)

Multi-dimensional arrays and Matrices are popular interview topics in programming technical interviews. Although practical applications for such …

Python Programming

How to Choose the Best Chart for Your Data

The amount of data at our fingers tips today can be overwhelming. How do you know what really matters? Data visualizations can help, but how can you …

IBM platform integrates data science and machine learning to boost enterprise AI

The firm also unveiled its Data Science Elite Team, a free consultancy service that helps companies get the most out of their AI initiatives.<p>Building …

How to Test AI models: An Introduction Guide for QA

The latest trends show that machine learning is one of the most rapidly developing fields in computer science. Unfortunately, it’s still unclear to …

How to rewrite your SQL queries in Pandas, and more

Introduction to Pandas, for developers already familiar with SQL.

Python Programming

Shape Context descriptor and fast characters recognition

Shape Context — is a scale & rotation invariant shape descriptor (not image).Today i will try to give you an idea how it works and why it so cool …

Python Programming

Self Driven Data Science — Issue #39

Here’s this weeks lineup of data-driven articles, stories, and resources delivered faithfully to your inbox for you to consume. Enjoy!<p><b>A Beginner’s</b> …

Data Science

Big data and advanced analytics: How the banking sector is keeping up

Big data and advanced analytics are at the center of how financial services institutions are equipping themselves to deliver better value to their …

Big Data

Introduction to Markov Chains

What are Markov chains, when to use them, and how they work

Data Science

Always start with a stupid model, no exceptions. – Insight Data

How to efficiently build Machine Learning powered products.<p><i>For more content like this, follow</i> <i>Insight</i> <i>and</i> <i>Emmanuel</i> <i>on Twitter.</i><p>Let’s start with the …

Understanding and interpreting your data set

Don`t jump into modelling. First, understand and explore your data!This is common advice for many data scientists. If your data set is messy, …

Machine Learning

Fundamentals of Data Visualization

17 Choosing the right visualization software<p>Throughout this book, I have purposefully avoided one critical question of data visualization: How do we …

Common Patterns for Analyzing Data

Data is often messy, and a key step to building an accurate model is a thorough understanding of the data you're working with.<p>Before I started …

Exploratory Analysis – When to Choose R, Python, Tableau or a Combination

(This article was first published on <b> R-Projects – Stoltzmaniac</b>, and kindly contributed to R-bloggers)Not all data analysis tools are created …

Databases

5 Reasons Data Scientists Should Adopt DevOps Practices

Enterprise software development teams have historically had trouble ensuring the code that runs well on a developer's machine also runs well in …

Big Data