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Why two similar functions can produce very different outcomes Photo by Pietro Jeng on Unsplash Intro In recent years, Swish has supplanted Relu in several high performing image classification models (e.g. Efficient-Net). However, it has not shown clear favor across all machine learning tasks. A very similar activation function, Gaussian Error Linea ...
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Lithology Prediction Using Deep Learning: Force 2020 Dataset: Part.1 (data visualization) Multiclass Classification: geology example The objective of this competition was to predict lithology labels from well logs, provided NDP lithostratigraphy and well X, Y position. In this work, it is attempted to have a standard approach, like other Machine Le ...
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Podcast David Roodman on what happens when AI pushes us off the edge of the map Editor’s note: This episode is part of our podcast series on emerging problems in data science and machine learning, hosted by Jeremie Harris. Apart from hosting the podcast, Jeremie helps run a data science mentorship startup called SharpestMinds . You can listen to th ...
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I think we have enough of them.
There are so many of the same shallow posts trying to explain all of machine learning in one stupid infographic and somehow they always end up getting a ton of likes.I don’t see how they are actually helpful to anyone though.If you actually want to help the community and want to make (or more likely steal) a littl ...
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“When should I hear back?” and other painful questions — answered with data The story of the job hunt, as told by actual data Avoid “when will I hear back” anxiety, and save yourself an awkward visit to the dentist — Photo courtesy of Unsplash One of the biggest problems with the job search process is a lack of actionable data. Without data, job se ...
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I come from a traditional engineering field, and here is my observation about ML publication practice lately:
I have noticed that there are groups of researchers working on the intersection of "old" fields such as optimization, control, signal processing and the like, who will all of a sudden publish a massive amount of paper that purports to so ...
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How I Am Learning Machine Learning — Week 2: Python and Pandas (Part Two) Last week we saw the first steps on how to display data in pandas on jupyter notebook, but there is still some work to do. Comparing two columns If we are analyzing a dataFrame there is the chance that we do not always want to see all the data but to just compare two columns ...
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Can we tell buses from cars using their trajectory data? This is a summary of a data-science project that aims to predict if a vehicle is either a car or a bus using machine-learning models and simulated time-series data. This project is based on data contained in this repository. The authors took work produced by the Communication Systems Departme ...
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Today ML Engineer and data scientist demand greatly outweighs the supply. Most of the students in beginning get intimidated when they hear the term Machine Learning they think it’s some fancy and complicated thing , let me assure you it’s quite simple once you understand it and if you just read this article it will definitely help in kickstarting y ...
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In this podcast Dr Phil Winder, CEO of Winder Research, sits down with InfoQ podcast co-host Charles Humble. They discuss: the history of Reinforcement Learning (RL); the application of RL in fields such as robotics and content discovery; scaling RL models and running them in production; and ethical considerations for RL. By Phil Winder
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Hello all,
I had some time between jobs so I wanted a hobby project where I can learn some Python. The result is a Twitter bot that is watching a bird feeder in my backyard for birds. If any birds are spotted, it tries to identify the species through a classification model. Both object detection and specie classification are done through existin ...
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Learn to correctly interpret the coefficients of Logistic Regression and in the process naturally derive its cost function — the Log Loss! Source: Unsplash Overview Logistic regression coefficients are somewhat different than the usual Linear Regression coefficients when it comes to interpretation. Models like Logistic Regression often win over the ...
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Azure Cognitive Search is a cloud search service that gives developers APIs and tools to build rich search experiences over private, heterogeneous content in web, mobile, and enterprise applications. It has multiple components, including an API for indexing and querying, seamless integration through Azure data ingestion, deep integration with Azure
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In this article, we scratch spam email classification using one of the simplest techniques called the Naive Bayes classification. Read the full story ...
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Introduction One of the most difficult tasks of building machine learning applications is deploying them to production. The ML.NET team is exploring ways to simplify the process and would like to hear your feedback. When it comes to deploying machine learning models as web services, The post Serve ML.NET Models as HTTP APIs with minimal configurati
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Part 1 of 3, Creating a Regression Model in Python Introduction Using the past to predict the future! Say hello to Regression Modeling! In this three-part series I will show you how to create, use, and check the validity of a regression model with python. To effectively cover the topic, I have broken the topic into the following parts. Blog 1 (this ...
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Jupyter notebooks are a dominant tool for data scientists, but they lack a number of conveniences for building reusable and maintainable systems. For machine learning projects in particular there is a need for being able to pivot from exploring a particular dataset or problem to integrating that solution into a larger workflow. Rick Lamers and Yann
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