Subscribe to DSC Newsletter

Andrea Manero-Bastin's Blog (57)

Regression analysis using Python

This article was written by Stuart Reid. 

 

This tutorial covers regression analysis using the Python StatsModels package with Quandl integration. For motivational purposes, here is what we are working towards: a regression analysis program which receives multiple data-set names from Quandl.com, automatically downloads the data, analyses it, and plots the results in a new window.…

Continue

Added by Andrea Manero-Bastin on December 8, 2019 at 6:30am — No Comments

R Package Install Troubleshooting

This article was written by Laura Ellis.

 

One of the reasons why I love R is that I feel like I’m constantly finding out about cool new packages through an ever-growing community of users and teachers. 

To understand the current state of R packages on CRAN, I ran some code provided by Gergely Daróczi on Github .  As of today there have been almost 14,000 R packages published on CRAN and the rate of…

Continue

Added by Andrea Manero-Bastin on December 1, 2019 at 6:30am — No Comments

How to build a deep learning model in 15 minutes

This article was written by Montana Low. 

 

An open source framework for configuring, building, deploying and maintaining deep learning models in Python.

As Instacart has grown, we’ve learned a few things the hard way. We’re open sourcing Lore, a framework to make machine learning approachable for Engineers and maintainable for Machine Learning Researchers.…

Continue

Added by Andrea Manero-Bastin on November 30, 2019 at 9:00am — No Comments

Introduction to Markov Chains

This article was written by Devin Soni.  

 

Markov chains are a fairly common, and relatively simple, way to statistically model random processes. They have been used in many different domains, ranging from text generation to financial modeling. A popular example is r/SubredditSimulator, which uses Markov chains to automate the creation of content for an entire subreddit. Overall, Markov Chains are conceptually quite intuitive,…

Continue

Added by Andrea Manero-Bastin on November 18, 2019 at 5:00am — 1 Comment

New Theory Cracks Open the Black Box of Deep Learning

This article was written by Natalie Wolchover.

 Even as machines known as “deep neural networks” have learned to converse, drive cars, beat video games and Go champions, dream, paint pictures and help make scientific discoveries, they have also confounded their human creators, who never expected so-called “deep-learning”…

Continue

Added by Andrea Manero-Bastin on November 1, 2019 at 5:30am — No Comments

How to Detect Objects with Deep Learning on Raspberry Pi

This article was written by Sarthak Jain.

 The real world poses challenges like having limited data and having tiny hardware like Mobile Phones and Raspberry Pis which can’t run complex Deep Learning models. This post demonstrates how you can do object detection using a Raspberry Pi. Like cars on a road,…

Continue

Added by Andrea Manero-Bastin on October 31, 2019 at 1:30pm — No Comments

SQL and RDBMS Basics

This article was originally posted here.

If you meet 10 people who have been in data science for more than 5 years, chances are that all of them would know of or would…

Continue

Added by Andrea Manero-Bastin on October 24, 2019 at 8:00am — No Comments

Semantic Image Segmentation with DeepLab in TensorFlow

This article was written by Liang-Chieh Chen and Yukun Zhu.

Semantic image segmentation, the task of assigning a semantic label, such as “road”, “sky”, “person”, “dog”, to every pixel in an image enables numerous new applications, such as the synthetic shallow depth-of-field effect shipped in the portrait mode of the Pixel 2 and Pixel 2 XL smartphones and …

Continue

Added by Andrea Manero-Bastin on October 24, 2019 at 7:30am — No Comments

5 Algorithms to Train a Neural Network

This article was written by Alberto Quesada.

 

The procedure used to carry out the learning process in a neural network is called the optimization algorithm (or optimizer). There are many different optimization algorithms. All have different characteristics and performance in terms of memory requirements, speed and…

Continue

Added by Andrea Manero-Bastin on October 20, 2019 at 2:00am — No Comments

Why Every Data Scientist Needs A Data Engineer

This article was written by Laurel Brunk.

Data scientists spend most of their time (up to 79%!) on the part of their job they hate most.

 The Role of…

Continue

Added by Andrea Manero-Bastin on October 20, 2019 at 2:00am — 2 Comments

When Bayes, Ockham, and Shannon come together to define machine learning

This article was written by Tirthajyoti Sarkar.

 

Acknowledgements

Thanks to my CS7641 class at Georgia Tech in my MS Analytics program, where I discovered this concept and was inspired to write about it. Thanks to Matthew Mayo for editing and re-publishing this…

Continue

Added by Andrea Manero-Bastin on October 15, 2019 at 12:30am — No Comments

Automated Speech Processing using Filter Banks and MFCCs

This article was written by Haytham Fayek.

Speech processing plays an important role in any speech system whether its Automatic Speech Recognition (ASR) or speaker recognition or something else. Mel-Frequency Cepstral Coefficients (MFCCs) were very popular features for a long time; but more recently, filter banks are becoming increasingly popular. In this post, I will discuss filter…

Continue

Added by Andrea Manero-Bastin on October 6, 2019 at 7:00am — No Comments

Machine Learning’s Limits (Part 1): Why machine learning works in some cases and not in others.

This article was written by Ed Sperling.

 

Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs. What follows are excerpts of that…

Continue

Added by Andrea Manero-Bastin on October 6, 2019 at 6:30am — No Comments

A Comprehensive Guide to Stochastic Gradient Descent Algorithms

This article was written by Giuseppe Bonaccorso.

 

Stochastic Gradient Descent (SGD) is a very powerful technique, currently employed to optimize all deep learning models. However, the vanilla algorithm has many limitations, in particular when the system is ill-conditioned and could never find the global minimum. In this post, we’re going to analyze how it…

Continue

Added by Andrea Manero-Bastin on September 30, 2019 at 3:00am — No Comments

Using Machine Learning to Solve Business Problems

This article was written by Soft Media Lab.

It has the following sections.

Contents

  • What is Machine Learning?
  • How to apply machine learning to…
Continue

Added by Andrea Manero-Bastin on September 24, 2019 at 6:30am — No Comments

Attacks against machine learning — an overview

This article was written by Elie Bursztein.

 

This blog post survey the attacks techniques that target AI (artificial intelligence) systems and how to protect against them.

At a high level, attacks against classifiers can be broken down into three types:

  • Adversarial inputs, which are specially crafted inputs that have been developed with the aim of…
Continue

Added by Andrea Manero-Bastin on September 24, 2019 at 2:30am — No Comments

The simplest explanation of machine learning you’ll ever read

This article was written by Cassie Kozyrkov.

 

You’ve probably heard of machine learning and artificial intelligence, but are you sure you know what they are? If you’re struggling to make sense of them, you’re not alone. There’s a lot of buzz that makes it hard to tell what’s science and what’s science fiction. Starting with the names…

Continue

Added by Andrea Manero-Bastin on September 21, 2019 at 9:00am — No Comments

Introduction to Various Reinforcement Learning Algorithms

This article was written by Steeve Huang.

 

Reinforcement Learning (RL) refers to a kind of Machine Learning method in which the agent receives a delayed reward in the next time step to evaluate its previous action. It was mostly used in games (e.g. Atari, Mario), with performance on par with or even exceeding humans. Recently, as the algorithm evolves with the combination of Neural Networks, it is capable…

Continue

Added by Andrea Manero-Bastin on September 9, 2019 at 12:30am — No Comments

Object Detection with 10 lines of code

This article was written by Moses Olafenwa.

One of the important fields of Artificial Intelligence is Computer Vision. Computer Vision is the science of computers and software systems that can recognize and understand images and scenes. Computer Vision is also composed of various aspects such…

Continue

Added by Andrea Manero-Bastin on August 31, 2019 at 10:30am — 1 Comment

What is AI: explaining it from different dimensions

This article was written by Swami Chandrasekaran.

Click on the picture below to zoom in. 

AI is a fascinating area and I personally feel it will not do justice to explain it without looking at it from…

Continue

Added by Andrea Manero-Bastin on August 11, 2019 at 7:30am — No Comments

Videos

  • Add Videos
  • View All

© 2019   Data Science Central ®   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service