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 …
Is the Data Analytics Era Coming to an End?
Author(s): Manmohan Singh Data Analytics, Opinion Importance of Text Analytics in NLP Source: Markus Spiske from Unsplash Can you recall, when the last time have you used text analytics? Or read an article about it on medium and other blogs? Do you know any …
YOLO V5 — Explained and Demystified
Last Updated on July 1, 2020 by Editorial Team Author(s): Mihir Rajput Computer Vision YOLO V5 — Explained and Demystified YOLO V5 — Model Architecture and Technical Details Explanation Source: https://pixabay.com/ From my previous article on YOLOv5, I received multiple messages and queries on how things …
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 …
Assumptions of Linear Regression — What Fellow Data Scientists Should Know
Author(s): Shaurya Lalwani Originally published on Towards AI. Photo by Marius Masalar on Unsplash Linear Regression is a linear approach to modeling the relationship between a target variable and one or more independent variables. This modeled relationship is then used for predictive …
Assumptions of Linear Regression — What Fellow Data Scientists Should Know
Author(s): Shaurya Lalwani Machine Learning Assumptions of Linear Regression — What Fellow Data Scientists Should Know Photo by Marius Masalar on Unsplash Linear Regression is a linear approach to modeling the relationship between a target variable and one or more independent variables. This modeled relationship is …
YOLO V5 — Explained and Demystified
Author(s): Mihir Rajput Originally published on Towards AI. Computer Vision YOLO V5 — Model Architecture and Technical Details Explanation Source: https://pixabay.com/ From my previous article on YOLOv5, I received multiple messages and queries on how things are different in yolov5 and other …
Performing a Market Basket Analysis with Machine Learning
Author(s): Michelangiolo Mazzeschi Improve Marketing with AI. Full code available at my repo Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Building Neural Networks with Python Code and Math in Detail — II
Author(s): Towards AI Editorial Team Originally published on Towards AI. Join us ↓ | Towards AI Members | The Data-driven Community Top highlight Source: Pixabay Last updated January 7, 2021 Author(s): Pratik Shukla, Roberto Iriondo Join Towards AI, by becoming a member, …
Generating Synthetic Sequential Data using GANs
Author(s): Armando Vieira Sequential data — data that has time dependency — is very common in business, ranging from credit card transactions to medical healthcare records to stock market prices. But privacy regulations limit and dramatically slow-down access to useful data, essential …
Building Neural Networks with Python Code and Math in Detail — II
Author(s): Pratik Shukla, Roberto Iriondo Source: Pixabay The second part of our tutorial on neural networks from scratch. From the math behind them to step-by-step implementation case studies in Python. Launch the samples on Google Colab. In the first part of our tutorial …
Content-Based Recommendation System using Word Embeddings
Author(s): Dhilip Subramanian Average Word2Vec and TF-IDF Word2Vec Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Do You Understand Gradient Descent and Backpropagation? Most Don’t.
Author(s): Michel Kana, Ph.D A simple mathematical intuition behind one of the commonly used optimization algorithms in Machine Learning. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
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