When Variance and Standard Deviation Fail to Explain Variability!
Author(s): Astha Puri Originally published on Towards AI. We all know the definition of variance — it helps us understand how dispersed the data points are, around the mean. If the data points are far off from the mean, we have larger …
Don’t believe ScoMo: What AI means for us in 2020+
Author(s): Dr. Adam Hart Originally published on Towards AI. © OpenClipart-Vectors courtesy Pixabay The history of the government of people is superficially a history of the tensions between personal liberty and social responsibility for the greater good. This is what we’re taught …
Top Restaurant Finder Nearby
Author(s): Chittal Patel Originally published on Towards AI. Photo by Jay Wennington on Unsplash Introduction In this project, I created a Basic Data Science Project namely Top Restaurant Finder which will give the top Restaurants near your address. I did explore the …
Generate Quotes with Web Scrapping, Glove Embeddings, and LSTM in Pytorch
Author(s): Lakshmi Narayana Santha Originally published on Towards AI. Introduction With the rise of advancement in research in NLP specially in Language Models, text generation – a classical machine learning task which solved using Recurrent Networks. In this article we walk through …
Building a Spam Detector Using Python’s NTLK Package
Author(s): Bindhu Balu Originally published on Towards AI. NTLK — Natural Language ToolKit In this part, we will go through an end to end walkthrough of building a very simple text classifier in Python 3. Our goal is to build a predictive …
4 Graph Neural Networks you Need to Know (WLG, GCN, GAT, GIN)
Author(s): Edward Ma Originally published on Towards AI. Top highlight Photo by Edward Ma on Unsplash We went through Knowledge Graph Embeddings and Random Walk in previous graph neural network stories. Knowledge graph embeddings train entity embeddings for downstream tasks. On the …
Why Batch Normalization Matters?
Author(s): Aman Sawarn Originally published on Towards AI. Understanding why batch normalization works, along with its intuitive elegance. Batch Normalization(BN) has become the-state-of-the-art right from its inception. It enables us to opt for higher learning rates and use sigmoid activation functions even …
How AI is Revolutionizing the Process of Fintech Firms?
Author(s): Kristy Hill Originally published on Towards AI. Top highlight AI is expanding the development of Fintech Companies and taking care of human issues, by increasing efficiency. How AI is Revolutionizing the Process of Fintech Firms? Artificial Intelligence has revolutionized the finance …
The Rickety Tripod of IBM’s AI Ethics
Author(s): Dr. Adam Hart Originally published on Towards AI. © EmTech 2017/MIT The greatest benefit of the English language is its greatest weakness. The same word can be used either very precisely or really very imprecisely with sometimes perplexing and even deathly …
Problem Framing: The Most Difficult Stage of a Machine Learning Project Workflow
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Framing the right problem to tackle with data in a real-world project is not very straightforward Top highlight Photo by You X Ventures on Unsplash In this article, I will discuss why …
Attention! Beginners, Theory: Challenging terms and Methods for Facial Features Recognition
Author(s): Surya Govind Originally published on Towards AI. Theory Explained ( Computer Vision ): Pattern recognition ( Facial Recognition ) with Challenges and possible methods Image by newsroom.cisco.com from Laurence Cruz Energy-saving tip folk: Better start with OpenCV-C++/ Python, https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec_tutorial.html is a …
How My Team of Undergrads Won a Data Science Competition for Graduate and Ph.D. Students
Author(s): Brandon Walker Originally published on Towards AI. The Challenge Statement Top highlight I think there are a few secrets to success in data science that I uncovered while doing the Texas A&M Institute of Data Science’s Competition. I’ll outline my experience …
EfficientDet: When Object Detection Meets Scalability and Efficiency
Author(s): Aniket Maurya Originally published on Towards AI. EfficientDet, a highly efficient and scalable state of the art object detection model developed by Google Research, Brain Team. It is not just a single model. It has a family of detectors which achieve …
Attention Beginners! Powerful Exposure of Eye Gaze Tracking Procedure
Author(s): Surya Govind Originally published on Towards AI. Explanation of the Existing system and steps required for eye gaze estimation Image from bdtechtalks.com by Ben Dickson. For your convenience, I have added a few importnt explanation links for the concepts that are …
Titanic Challenge — Machine Learning for Disaster Recovery — Part 2
Author(s): Bindhu Balu Originally published on Towards AI. Source: Pxfuel Part-2 — Predictive Model Building Code Location: https://github.com/BindhuVinodh/Titanic—Predictive-Model-Building II — Feature engineering In the previous part, we flirted with the data and spotted some interesting correlations. In this part, we’ll see how …
Recent Posts
