With traditional TV viewing on the decline, we discuss several ways Big Data and Machine Learning can assist with online video, including redefining user recommendations, improving video buffering and leveraging MAM orchestration.
What follows is then an effort to draw an architecture to access knowledge on AI and follow emergent dynamics, a gateway of pre-existing knowledge on the topic that will allow you to scout around for additional information and eventually create new knowledge on AI.
Join data and analytics leaders at CAO Fall in Boston, Oct 8-11, the platform to guide you through transformation and help you innovate within your business. KDnuggets readers save $100 on your pass using discount code KDNUGGETS100.
Career fairs are a great way to get your feet wet if you’re just starting your data science career, or to be exposed to newer trends and emerging organizations if you’re already established. What other ways are career fairs beneficial?
A well-known model that learns vectors or words from their co-occurrence information is GlobalVectors (GloVe). While word2vec is a predictive model — a feed-forward neural network that learns vectors to improve the predictive ability, GloVe is a count-based model.
Information on how to download this whitepaper, which provides a view into how streaming data analytics is different from traditional analytics and thus have unique data processing needs that translate into absolute must-haves for the streaming analytics platform.
In this blog, we’ll try to understand the different interpretations of this “distant” notion. We will also look into the outlier detection and treatment techniques while seeing their impact on different types of machine learning models.
I reported that you can multiply the speed of common (fast) random number generators such as PCG and xorshift128+ by a factor of three or four by vectorizing them using SIMD instructions. Is this actually useful in practice?
We discuss the key considerations in selecting the optimal AI infrastructure required to train deep neural networks for safe self-driving systems, including data requirements and computing performance needed, and how to use NVIDIA DGX-1 for training autonomous vehicles.
Predictive Analytics World for Government, Sep 18-19, Washington DC, is a practically-focused, vendor neutral conference that highlights case studies and emerging trends of how government agencies are currently using data analytics to solve real world problems.
Also: Why Automated Feature Engineering Will Change the Way You Do Machine Learning; Interpreting a data set, beginning to end; Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code; Emotion and Sentiment Analysis: A Practitioners Guide to NLP
The vast majority of text classification articles and tutorials on the internet are binary text classification such as email spam filtering and sentiment analysis. Real world problem are much more complicated than that.
Open-source Dash lets you wrap a GUI around that analytical code, without leaving the familiarity of Python. Explore your data with rich, interactive drop-down menus, sliders, and other components, all in the web browser.
Sentiment analysis is widely used, especially as a part of social media analysis for any domain, be it a business, a recent movie, or a product launch, to understand its reception by the people and what they think of it based on their opinions or, you guessed it, sentiment!
Both athletes and machines deal with inter-twined complex systems (where the interactions of one complex system can have a ripple effect on others) that can have significant impact on their operational effectiveness.
Learn more about the hottest trends that are shaping the future and beyond at Big Data Summits in London and Barcelona. Deep dive into the topics that will shake up your industry and encourage innovation at your company. Enjoy £250 off all two-day events with code KD250.
This comprehensive cheat sheet will assist Docker users, experienced and new, in getting containers up-and-running quickly. We list commands that will allow users to install, build, ship and run Docker containers.
At the most basic level, probability seeks to answer the question, "What is the chance of an event happening?" To calculate the chance of an event happening, we also need to consider all the other events that can occur.
Detailed knowledge of your data is key to understanding it! We review several important methods that to understand the data, including summary statistics with visualization, embedding methods like PCA and t-SNE, and Topological Data Analysis.
Named entity recognition (NER) , also known as entity chunking/extraction , is a popular technique used in information extraction to identify and segment the named entities and classify or categorize them under various predefined classes.
In this on-demand webinar, you’ll get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why you should be running on a CPU.
In this post, I will explore the implementation of reinforcement learning in trading. The Financial industry has been exploring the applications of Artificial Intelligence and Machine Learning for their use-cases, but the monetary risk has prompted reluctance.
Auto-Keras is an open source "competitor" to Google’s AutoML, a new cloud software suite of Machine Learning tools. It’s based on Google’s state-of-the-art research in Neural Architecture Search (NAS).
In this post, we'll walk through how to set up a data science environment on Google Cloud Platform (GCP). Because of the economy of scale that cloud hosting companies provide, individuals or teams can affordably access powerful computers.
Learn a process for discovering the data and analytics needs of your users using user stories, use cases and mapping to data sources; Strategies for balancing priorities and managing expectations, and more.
Read this eBook to learn: How deep learning enables image classification, sentiment analysis, and other advanced analysis techniques and get a a starter workflow for building and training deep learning models.
Whether you're a novice data science enthusiast setting up TensorFlow for the first time, or a seasoned AI engineer working with terabytes of data, getting your libraries, packages, and frameworks installed is always a struggle. Learn how datmo, an open source python package, helps you get started in minutes.
Also: Only Numpy: Implementing GANs and Adam Optimizer using Numpy; Understanding Language Syntax and Structure; Eight iconic examples of data visualisation; 5 Data Science Projects That Will Get You Hired in 2018; Seven Practical Ideas For Beginner Data Scientists
Win KDnuggets pass to AI Conference in San Francisco, where you'll join the leading minds in AI: Kai-Fu Lee, Meredith Whittaker, Peter Norvig, Dawn Song, David Patterson, Huma Abidi, Matt Wood, and more. Enter by Aug 18.
Download Figure Eight's new ebook, The Essential Guide to Training Data, and you'll learn about the advantages of using more data, the differences between having lots of big data and having labeled data, and some great open datasets to bootstrap your model.
Cross-validation is frequently used to train, measure and finally select a machine learning model for a given dataset because it helps assess how the results of a model will generalize to an independent data set in practice.
Key information regarding The Alteryx Analytics Revolution Summit roadshow in Australia, including dates, guest speakers, livestream information and how you can register for the roadshow closest to you.
As someone who has been there, I’d like to outline a few practical ideas to help junior data scientists get started at a small software company. The steps were drawn from my personal journey and that of others before me.
Also: Eight iconic examples of data visualisation; Selecting the Best Machine Learning Algorithm for Your Regression Problem; Intuitive Ensemble Learning Guide with Gradient Boosting; Eight iconic examples of data visualisation; Data Scientist Interviews Demystified
By using the within-cluster sum of squares as cost function, data points in the same cluster will be similar to each other, whereas data points in different clusters will have a lower level of similarity.
This event connects C-suite, Heads and Managers of Mine Operations and Mining Equipment, Technology and Services providers to debate and define the future mining landscape on a strategic level. Special KDnuggets discount.
In this live webinar (Aug 8, 1PM EST), discover research findings, best practices for AI adoption, use cases on the growth of machine learning, and how automated machine learning technologies make AI more accessible to organizations of all sizes.
Also: Comparison of Top 6 Python NLP Libraries; Math for Machine Learning: Open Doors to Data Science and Artificial Intelligence; Building A Data Science Product in 10 Days; Data Scientist was the sexiest job of the 21st century until...; Automated Machine Learning vs Automated Data Science
This article covers defining statistics, descriptive statistics, measures of central tendency, and measures of spread. This article assumes no prior knowledge of statistics, but does require at least a general knowledge of Python.