Feature Selection in Machine Learning
Author(s): Shaurya Lalwani Machine Learning Photo by Louis Hansel @shotsoflouis on Unsplash In the real world, data is not as clean as it’s often assumed to be. That’s where all the data mining and wrangling comes in; to build insights out of the …
Regression Line with Mathematics for the Linear Regression
Author(s): Gul Ershad Originally published on Towards AI. The equation of Intercept a: Regression is a prediction where the target is continuous and its applications are several. It is the simplest parametric model. Every data-set is given in a pair consisting of …
Learning TensorFlow 2: Use tf.function and Forget About tf.Session
Author(s): Irfan Danish A comparison betweeen tf.function & tf.Session along with the explanantion of AutoGraph Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
AI Disruption is Starting Already
Author(s): Michelangiolo Mazzeschi Originally published on Towards AI. Standard Procedure AI disruption has already begun. Look at tools such as autoML or Lobe.They will soon eat out the demand for ML engineers at the lower end of the competence distribution. Not long …
Exploratory Data Analysis (EDA) using Pyspark
Author(s): Vivek Chaudhary Originally published on Towards AI. Data Analytics, Python The objective of this article is to perform analysis on the dataset and answer some questions to get the insight of data. We will learn how to connect to Oracle DB …
Scraping Your Medium Stories
Author(s): Joaquin de Castro Originally published on Towards AI. Data Mining, Programming While learning about and exploring the power of web scraping In the “good old days” Medium allowed us to have custom websites for our publications. Unfortunately, this functionality has been …
K-means Clustering in a Nutshell
Author(s): Ramya Vidiyala The simplest clustering algorithm Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Sentiment Analysis — ML project from Scratch to Production (Web Application)
Author(s): Shareef Shaik Originally published on Towards AI. Metrics used : A glimpse of the application we are going to build. When I started learning Data science, I always get lost in the amount of material it offers. After learning it for …
First Principles Approach in Data Science
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. a. Problem Framing Image Source: Pexels The first principles approach to problem-solving is the act of breaking a problem down to the fundamental parts and building up from there. This method is …
ResNet Architecture: Deep Learning with PyTorch
Author(s): Satyam Kumar Singh Originally published on Towards AI. Deep Learning From winning ImageNet Large Scale Visual Recognition Challenge (ILSVRC) in 2015 till now ResNet Architecture has been remarkable in the field of Data Science. Apart from ILSVRC, ResNet also won Detection …
AI Generates 3D high-resolution reconstructions of people from 2D images | Introduction to PIFuHD
Author(s): Louis Bouchard Originally published on Towards AI. This AI Generates 3D high-resolution reconstructions of people from 2D images! It only needs a single image of you to generate a 3D avatar that looks just like you, even from the back! The …
K-means Clustering from Scratch
Author(s): Sayar Banerjee NumPy is all you need Photo by h heyerlein on Unsplash An Algorithm must be seen to be believed — Donald Knuth Overview The science of Machine Learning can be broadly classified into two categories: Supervised learning Unsupervised learning In this blog post, we …
Supporting the Math Behind Supporting Vector Machines!
Author(s): Daksh Trehan A quick tour to SVM constituting mathematical & theoretical explanation along with from the scratch implementation. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Why Choose Random Forest and Not Decision Trees
Last Updated on November 17, 2020 by Editorial Team Author(s): Daksh Trehan A concise guide to Decision Trees and Random Forest. Decision trees belong to the family of the supervised classification algorithm. They perform quite well on classification problems, the decisional path is …
Clustering : What it is? When to use it?
Last Updated on July 1, 2020 by Editorial Team Author(s): Daksh Trehan Machine Learning Clustering: What Is It and When To use it? A comprehensive guide to K-Means, K-Means++, and DBSCAN. Clustering is a Machine Learning technique whose aim is to group the data …
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