Reduce training time for deep neural networks by using many GPUs Marenostrum Supercomputer — Barcelona Supercomputing Center https://bsc.es (This post will be used in my master course SA-MIRI at UPC Barcelona Tech with … Read more
Some practical examples, tips, and thoughts on supervised ML Earlier this year, through my MBA program at Cornell Tech, I took a great intro course on Machine Learning with a … Read more
Rethinking the problem I decided to pivot and try something new. It seemed to me that there was a clear disconnect between the odd look of the training data and images … Read more
Meng LiBlockedUnblockFollowFollowing Dec 17 Ever seen a destination map in Tableau? It’s usually used to show the tracks of flights, bus maps, traffic and so on. There are loads of … Read more
What is mlFlow? mlFlow is a framework that supports the machine learning lifecycle. This means that it has components to monitor your model during training and running, ability to store models, … Read more
Storage endpoints Perhaps the more relevant part of AzureStor for most users is its client interface to storage. With this, you can upload and download files and blobs, create containers … Read more
Indeed, true personalization understands customers at a deeper level — their real-time intent, purchasing history, preferences and complex shopping journeys. It then utilizes these insights to tailor congruent, 1:1 interactions across channels. … Read more
Introduction Playing around with PyTorch and R Shiny resulted in a simple Shiny app where the user can upload a flower image, the system will then predict the flower species. … Read more
Let’s take a look at the following diagram that illustrates the purposes of the specific layers in the CNN. As we can see above, starting from the left we are … Read more
Identifying firms with intentional distortion of financial statements is a challenging and exciting problem among auditors, banks and investors who rely on financial information to make decisions. Yet it is … Read more
We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive … Read more
Data Collection There are three datasets we’re using to run this experiment: A dataset we’ll collect ourselves that includes over 3400 song lyrics between 1970 and 2018. A list of … Read more
For anyone who has been paying attention, it will not have gone unnoticed that the past year has seen a dramatic expansion in the use of face recognition technology, including … Read more
In a project of developing PPNR balance projection models, I tried to use the Phillips-Ouliaris (PO) test to investigate the cointegration between the historical balance and a set of macro-economic … Read more
Explore further the world of data science, machine learning and artificial intelligence We are on a mission to get the best content relevant to data science, machine learning, and artificial … Read more
Article jointly written by Arthur Pesah and Antoine Wehenkel Motivation There are usually two ways of coming up with a new scientific theory: Starting from first principles, deducing the consequent … Read more
How to conceptualize and implement effective data science projects Results, not hype Motivation The more I delve in data science, the more convinced I am that companies and data science practitioners must … Read more
Using Keras and TensorFlow.js to classify seven types of skin lesions Alex YuBlockedUnblockFollowFollowing Dec 16 After doing research on Convolutional Neural Networks, I became interested in developing an end-to-end machine learning … Read more
Learn how to Deal with Anxiety. When you start researching how to become a data scientist, you will discover an unfortunate fact about the profession. Namely, that becoming a data scientist … Read more
Ho, ho, ho! It’s almost Christmas time and I don’t know about you, but I can’t wait for it! And what can be a better way of killing the waiting … Read more
Advanced NLP techniques for deep learning With the problem of Image Classification is more or less solved by Deep learning, Text Classification is the next new developing theme in deep learning. … Read more
This report describes several R packages that allow HTML content to be rendered as part of an R plot. The core package is called ‘layoutEngine’, but that package requires a … Read more
In a new paper in Monthly Weather Review, minimum CRPS and maximum likelihood estimation are compared for fitting heteroscedastic (or nonhomogenous) regression models under different response distributions. Minimum CRPS is … Read more
Dec 16, 2018 Source: Dark Reading Background Our project was inspired by Jamie Ryan Kiros who created a model trained on 14 million romance passages to generate a short romantic story … Read more
Opening up a Colab Notebook When using Colab for the first time, you can launch a new notebook here: Once you have a notebook created, it’ll be saved in your Google … Read more
Flask API, Document Classification, Spam Filter By far, we have developed many machine learning models, generated numeric predictions on the testing data, and tested the results. And we did everything offline. … Read more
The origin of logic theory starts at the concept of an argument. The majority of logic textbooks contain an opening, central definition for an argument — one that likely sounds much like … Read more
Yes, SQL still exists During the years of working with telecom data my folder with code snippets collected a lot of reusable examples. And it is not about “SELECT * FROM … Read more
In our last note we used wrapr::qe() to help quote expressions. In this note we will discuss quoting and code-capturing interfaces (interfaces that capture user source code) a bit more. … Read more
Dec 16, 2018 Art of Generative Adversarial Networks Code link for all the work mention in the post:- We had this pleasure of working on Generative adversarial network project for … Read more
Progressively growing GANs enables them to get bigger and more stable The people in the high resolution images above may look real, but they are actually not — they were synthesized by a … Read more
How to take a map visualization to the next level. First, I will cover two reasons why visualizing data using maps is often compelling to an audience. Then, I will cover … Read more
Inorganic knowledge traditions with model-based reinforcement learning This essay explores the concept of inorganic knowledge traditions capable of sequential improvement using model based reinforcement learning Many behavioral economists presently believe … Read more
The profession of reality is moving into the 21st century, and as you can imagine home listings are flooding the internet. If you have ever looked at buying a home, … Read more
3. Model Building in R I have used the dataset which contains the details of 2,201 flights. The descriptions of each variable are as below. 3.1) Datasets schedtime : the scheduled time … Read more
As a newbie to machine learning most people get excited when their training error starts reducing. They try hard further and it starts reducing even further, their excitement knows no … Read more
Project by David Chen, Ashwin Gupta, Shruthi Krish, Raghav Prakash, Wei Wang Twitter is a social media platform that millions of users use to share updates about their lives. Often, … Read more
Exploring an important healthcare performance metric Photo by Hush Naidoo on Unsplash Project Overview Predictive analytics is an increasingly important tool in the healthcare field since modern machine learning (ML) methods … Read more
Using TensorFlow probability for Hamiltonian Sampling Free photo from https://pixabay.com One type of criticism I received for the previous work on project estimation is that the log-Normal distribution has short … Read more
This article focuses on how to utilize a popular open source database “Influxdb” along with spark-structured streaming to process, store and visualize data in real time. Here, we will go … Read more
Do you subscribe to the Data is Plural newsletter from Jeremy Singer-Vine? You probably should, because it is a treasure trove of interesting datasets arriving in your email inbox. In … Read more
Our linl package for writing LaTeX letter with (R)markdown had a fairly minor release today, following up on the previous release well over a year ago. This version just contains … Read more
The law has language at its heart, so it’s not surprising that software that operates on natural language has played a role in some areas of the legal profession for … Read more
Keras is an API used for running high-level neural networks. The model runs on top of TensorFlow, and was developed by Google. In this particular example, a neural network will … Read more
I tried my hand at using the R package, randomForest to create two regression models for tree height and basal area based off some lidar and field-collected data in the … Read more
I will be pushing a new version of futile.logger (version 1.5) to CRAN in January. This version introduces a number of enhancements and fixes some bugs. It will also contain … Read more
Generate characters from Alice in Wonderland Introduction Text generation is a popular problem in Data Science and Machine Learning, and it is a suitable task for Recurrent Neural Nets. This … Read more
Introduction to Plotly Plotly is a company that makes visualization tools including a Python API library. (Plotly also makes Dash, a framework for building interactive web-based applications with Python code). For … Read more
The first and most important step of our journey: As I have said before, we are going to simply ask questions that will guide us to build an image classifier. For … Read more
SRGAN Results from Ledig et al. [3] Generative adversarial networks (GANs) have found many applications in Deep Learning. One interesting problem that can be better solved using GANs is super-resolution. Super-resolution … Read more