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All Blog Posts Tagged 'dsc_graph' (65)

Network Graph Visualizations with DOT

Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs. Nearly thirty years ago, AT&T produced a set of libraries called graphviz which were…

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Added by Kurt A Cagle on November 29, 2020 at 2:00pm — No Comments

(With Images) Know everything about GANs (Generative Adversarial Network) in depth

Let’s understand the GAN(Generative Adversarial Network).

Generative Adversarial Networks were invented in 2014 by Ian Goodfellow(author of best Deep learning book in the market)  and his fellow researchers. The…

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Added by Sameer Nigam on November 10, 2020 at 8:02am — No Comments

Multi-stage heterogeneous ensemble meta-learning with hands-off demo

In this blog, I will introduce a R package for Heterogeneous Ensemble Learning (Classification, Regression) that is fully automated. It significantly lowers the barrier for the practitioners to apply heterogeneous ensemble learning techniques in an amateur fashion to their everyday predictive problems.…

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Added by Ajay Arunachalam on November 7, 2020 at 1:50am — No Comments

A taxonomy of explainable (XAI) AI models

I am reading a very interesting paper called Principles and Practice of Explainable Machine Learning by

Vaishak Belle (University of Edinburgh & Alan Turing Institute) and Ioannis Papantonis (University of Edinburgh) which presents a taxonomy of explainable AI (XAI).

 

XAI is a complex subject…

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Added by ajit jaokar on November 6, 2020 at 2:00pm — No Comments

Data Science Movies Recommendation System

Nearly everybody wants to invest their recreation energy to watch motion pictures with their loved ones. We as a whole have a similar encounter when we sit on our lounge chair to pick a film that we will watch and go through the following two hours yet can't discover one following 20 minutes. It is so baffling. We unquestionably need a PC operator to give film proposals to us when we have to pick a film and spare our time.

Evidently, a film suggestion specialist has just…

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Added by Sriram K on November 2, 2020 at 6:00am — No Comments

The MLOps Stack

What is MLOps (briefly)

MLOps is a set of best practices that revolve around making machine learning in production more seamless. The purpose is to bridge the gap between experimentation and production with key principles to make machine learning reproducible, collaborative, and continuous.

MLOps is not dependent on a single technology or platform. However, technologies play a significant role in practical…

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Added by Henrik Skogström on October 26, 2020 at 12:57am — No Comments

Genius Tool to Compare Best Time-Series Models For Multi-step Time Series Modeling

Predict Number of Active Cases by Covid-19 Pandemic based on Medical Facilities (Volume of Testing, ICU beds, Ventilators, Isolation Units, etc) using Multi-variate…

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Added by Sharmistha Chatterjee on October 17, 2020 at 10:30pm — No Comments

AI is Driving Software 2.0… with Minimal Human Intervention

The future of software development will be model-driven, not code-driven.

Now that my 4th book (“The Economics of Data, Analytics and Digital Transformation”) is in the hands of my publisher, it’s time to get back to work investigating and sharing new learnings.  In this blog I’ll take on the subject of Software 2.0.  And thanks Jens for the push in this direction!

Imagine trying to distinguish a dog from other animals in a photo…

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Added by Bill Schmarzo on October 15, 2020 at 6:21am — No Comments

Cross-validation and hyperparameter tuning

Introduction

Almost every machine learning algorithm comes with a large number of settings that we, the machine learning researchers and practitioners, need to specify. These tuning knobs, the so-called hyperparameters, help us control the behavior of machine learning algorithms when optimizing for performance, finding the right balance between bias and variance. Hyperparameter tuning for performance optimization is an art in itself,…

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Added by Andrea Manero-Bastin on October 14, 2020 at 5:00am — No Comments

The Neural Network Zoo

This article was written by Fjodor Van Veen. 

With new neural network architectures popping up every now and then, it’s hard to keep track of them all. Knowing all the abbreviations being thrown around (DCIGN, BiLSTM, DCGAN, anyone?) can be a bit overwhelming at first.

So I decided to compose a cheat sheet containing many of those architectures. Most of these are neural networks, some are completely different beasts. Though all of these…

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Added by Andrea Manero-Bastin on September 30, 2020 at 11:00am — No Comments

Deep Learning Explained in 4 Simple Facts

Yesterday, I talked about Machine Learning, and the huge impact it will have in the world in the future. Today, I’d like to talk about a similar paradigm, that often gets mixed up with it, but that is not the same thing at all. I’m talking about Deep learning.

First off, let me say: this topic is vast. In my article, I’ll try to boil down the main facts, but be warned, you should investigate the matter on your own to learn more.

Hope I can set…

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Added by Andrea Manero-Bastin on September 15, 2020 at 1:00am — No Comments

Understanding of Artificial Neural Networks

Introduction

Artificial neural networks are based on collection of connected nodes, and are designed to identify the patterns. They are part of deep learning, in which computer systems learn to recognize patterns and perform tasks, by analyzing training examples. For example an object recognition system can be fed to thousands of labeled images of houses, cars, traffic signals, animals etc. and would…

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Added by Kamal Jain on August 11, 2020 at 5:00am — No Comments

Sentiment Analysis using Deep Learning

Introduction

The growth of the internet due to social networks such as facebook, twitter, Linkedin,  instagram etc. has led to significant users interaction and has empowered users to express their opinions about products, services, events, their preferences among others. It has also provided opportunities to the users to share their wisdom and experiences with each other. The faster development of social networks is causing explosive growth of digital content. It has…

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Added by Kamal Jain on August 7, 2020 at 12:30am — No Comments

How Milvus Implements Dynamic Data Update and Query

Milvus is an open-source vector similarity search engine powered by approximate nearest neighbor search (ANNS) algorithms such as Faiss, NMSLIB, and Annoy. 

To make a vector search more intuitive and easy to use, we introduced TableFile and metadata in Milvus.

In this article, we will mainly describe how vector data are recorded in the memory of Milvus, and how these records are maintained.

Below are our main design goals:

  1. The efficiency of data…
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Added by Kate Shao on July 29, 2020 at 10:32pm — No Comments

Vector Similarity Search Engine

Milvus aims to achieve efficient similarity search and analytics for massive-scale vectors. A standalone Milvus instance can easily handle vector search for billion-scale vectors. However, for 10 billion, 100 billion, or even larger datasets, a Milvus cluster is needed. The cluster can be used as a standalone instance for upper-level applications and can meet the business needs of low latency, high concurrency for massive-scale data. A Milvus cluster can resend requests, separate reading…

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Added by Kate Shao on July 24, 2020 at 9:30pm — No Comments

Managing Data in Massive-Scale Vector Search Engine



How data management is done in Milvus…

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Added by Kate Shao on June 8, 2020 at 11:27pm — No Comments

Information Theory (Turbo Codes) & Bayesian Networks

An error correcting code (ECC) is a way of controlling errors in data that is being transmitted over an unreliable or noisy communication channel. In an ECC, the sender encodes the message with redundant information. The receiver is able to detect a limited number of errors, and to correct these errors without retransmission.

Turbo codes are a class of ECC that approach very closely the theoretical…

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Added by Robert R. Tucci on June 4, 2020 at 4:04pm — No Comments

Deploy Your First Serverless AWS ML Solution Fast

Introduction to SageMaker

I’ve been working with AWS SageMaker for a while now and have enjoyed great success. Creating and tuning models, architecting pipelines to support both model development and real-time inference, and data lake formation have all been made easier in my opinion.  AWS has proven to be an all encompassing solution for machine learning use cases, both batch and real-time, helping me decrease time to…

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Added by Jeff Diaz on June 2, 2020 at 12:00pm — No Comments

The Easiest Way to Search Among 1 Billion Image Vectors And Why Vector Search Is Important?

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Added by Kate Shao on May 26, 2020 at 6:00pm — No Comments

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