Building a Custom Image Dataset for an Image Classifier
Author(s): Dhilip Subramanian Showcasing an easy way to build a custom image dataset using google images. Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Local Binary Pattern for The Evaluation of Surface Quality of Dissimilar Friction Stir Welded Joints
Author(s): Akshansh Mishra Originally published on Towards AI. Engineering, Machine Learning Local Binary Pattern for The Evaluation of Surface Quality of Dissimilar Friction Stir Welded Joints Friction Stir Welding process is an advanced solid-state joining process which finds application in various industries …
Local Binary Pattern for The Evaluation of Surface Quality of Dissimilar Friction Stir Weldedβ¦
Author(s): Akshansh Mishra Engineering, MachineΒ Learning Local Binary Pattern for The Evaluation of Surface Quality of Dissimilar Friction Stir WeldedΒ Joints Friction Stir Welding process is an advanced solid-state joining process which finds application in various industries like automobiles, manufacturing, aerospace, and railway firms. …
How do Neural Networks learn?
Author(s): Dorian Lazar Going downhill on the loss landscape Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Bias & Variance in Machine Learning
Author(s): Shaurya Lalwani Originally published on Towards AI. Photo by Etienne Girardet on Unsplash Linear Regression is a machine learning algorithm that is used to predict a quantitative target, with the help of independent variables that are modeled in a linear manner, …
Bias & Variance in Machine Learning
Author(s): Shaurya Lalwani Machine Learning Photo by Etienne Girardet onΒ Unsplash Linear Regression is a machine learning algorithm that is used to predict a quantitative target, with the help of independent variables that are modeled in a linear manner, to fit a line …
Google Stock prediction using Multivariate LSTM Neural Network
Author(s): Michelangiolo Mazzeschi Originally published on Towards AI. Interpolation Not long ago I published a similar article on how to use LSTMs to make Stock predictions using a Vanilla Neural Network. Because I wanted to minimize the complexity of the problem, I …
Google Stock prediction using Multivariate LSTM
Author(s): Michelangiolo Mazzeschi Using a Vanilla LSTM to predict Google Stock prices Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Mythbusting 5G
Author(s): Jasper Ruijs — A thoughtful overview of the heated debate Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
NLP News Cypher | 07.26.20
Author(s): Ricky Costa Originally published on Towards AI. Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher U+007C 07.26.20 Primus The Liber Primus is unsolved to this day. A book of 58 pages written in Runes, …
NLP News Cypher | 07.26.20
Author(s): Quantum Stat Photo by Will Truettner onΒ Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER Primus The Liber Primus is unsolved to this day. A book of 58 pages written in Runes, of which, its bewildering encryption continues to haunt hacker gunslingers around …
Digit Classification using Tensorflow, Keras
Author(s): Michelangiolo Mazzeschi Full code available at my repo. Sources at this link. Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Why do We Need Activation Functions in Neural Networks?
Author(s): Dorian Lazar Activation functions motivated by examples Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Building a super-resolution image web-app
Author(s): Aanisha Bhattacharyya This is a web-app trained on SRCNN model. On giving an image as input, it reconstructs a higher resolution image of the same. I made this… Continue reading on Towards AIβββMultidisciplinary Science Journal Β» Published via Towards AI …
Deep Insights Into K-nearest Neighbors
Author(s): Palak Machine Learning Photo by ZdenΔk MachΓ‘Δek onΒ Unsplash Introduction K-nearest neighbors(in short KNNs) are a robust yet straightforward supervised machine learning algorithm. Though its regression variant also exists, weβll only discuss its classification form. KNN is a non-parametric lazy learning algorithm. …
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