AI creating Human-Looking Images and Tracking Artificial Intelligence Programs in 2020
Author(s): David Yakobovitch Machine Learning Transforming Veterans Benefits Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Building a Quantize Aware Trained Deep Learning Model
Author(s): Renu Khandelwal Learn what is Quantization, different types of Quantization, and how to build a TFLite model using Quantize Aware Training. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Campus Recruitment: EDA and Classification — Part 2
Author(s): Durgesh Samariya Day 15 of 100 Days of Data Science Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Opening the Black Box with Explainable AI [Hands-on]
Author(s): Frederik Bussler Explaining AI that forecasts wind energy production. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Shaping the Future Human Experience
Author(s): Andreea Bodnari AI drives efficiency in economic or settings. But it can also assist with personal development and human understanding. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Neural Networks from Scratch (A brief Introduction for Beginners)
Author(s): Pratik Kumar Understanding the concepts along with the implementation of neural networks using Python and its powerful library — Numpy. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Plant Disease Detection using Faster R-CNN
Author(s): Amrith Coumaran Deep Learning Faster R-CNN was first introduced in 2015 and is also a part of the R-CNN family. Compared to its predecessor, Faster R-CNN proposes a novel Region Proposals Network (RPN) and provides better performance and computational efficiency. The …
Learning Curves
Author(s): NVS Yashwanth Photo by Isaac Smith on Unsplash Machine Learning Evaluating machine learning models the right way Learning curves are useful in analyzing a machine learning model’s performance over various sample sizes of the training dataset. To understand learning curves, it is important to …
ECCV 2020 Best Paper Award | A New Architecture For Optical Flow
Author(s): Louis Bouchard Computer Vision, Research Photo by Cris Ovalle on Unsplash ECCV 2020 Best Paper Award Goes to Princeton Team.They developed a new end-to-end trainable model for optical flow.Their method beats state-of-the-art architectures’ accuracy across multiple datasets and is way more efficient. They …
Azure Cognitive Services Sentiment Analysis V3— Using PySpark
Author(s): Rory McManus What is Azure Cognitive Services — Text Analytics? Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Time Value of Money Easily Explained
Author(s): Michelangiolo Mazzeschi A conceptual explanation of TVM, why do we use it? Full code available at my repo. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
A Brief Introduction to Pairs Trading
Author(s): Abhinav Raghunathan A sort-of-deep dive into one of the many successful strategies employed by trading firms around the world. Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Analyzing CitiBike Data: EDA
Author(s): Sujan Shirol Getting the most out of Matplotlib and Seaborn Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
What is Unpacking in Python
Author(s): Chetan Ambi Understanding unpacking in Python with examples Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …
Develop Your Own K Mean Clustering Algorithm from Scratch in Python and Use It
Author(s): Rashida Nasrin Sucky An Unsupervised Machine Learning Algorithm from Scratch and Learn to Use It for Dimensional Reduction of an Image Continue reading on Towards AI — Multidisciplinary Science Journal » Published via Towards AI …