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Aaweg-I

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Deep Learning concepts for Medical Imaging — A shallow overview

U-Net Architechture (src: https://arxiv.org/abs/1505.04597) In this article I go through a few DL concepts used in Medical Imaging. This is a very limited piece, and depends highly on (can be considered a limited summary of) this paper: [https://arxiv.org/abs/1702.05747]. …

Deep Learning

7 min read

Deep Learning concepts for Medical Imaging — A shallow overview
Deep Learning concepts for Medical Imaging — A shallow overview
Deep Learning

7 min read


Dec 9, 2022

Choosing a Cloud Computing Platform for your enterprise

Being an ML Leader — We cannot do away with clouds. From the perspective of an enterprise, Cloud computing services do not accrue an upfront investment. We get advanced hardware without having to purchase it, and pay per second basis. They give us access to an on-demand large-scale computing capacity, making it possible to distribute…

Cloud Services

3 min read

Choosing a Cloud Computing Platform for your enterprise
Choosing a Cloud Computing Platform for your enterprise
Cloud Services

3 min read


Dec 9, 2022

Computer Vision with Neural Networks — an Overview

Terms, buzzwords and definitions are carefully worded. — Computer vision algorithms analyze certain criteria in images and videos and apply learned interpretations to predictive or decision-making tasks. Image processing is not same as computer vision. It is about modifying or enhancing images, like optimizing brightness or contrast, increasing resolution, blurring sensitive information, or cropping. …

Computer Vision

3 min read

Computer Vision with Neural Networks — an Overview
Computer Vision with Neural Networks — an Overview
Computer Vision

3 min read


Dec 9, 2022

AWS: SageMaker for Machine Learning (An Amazon Web Services product)

With SageMaker, we just need to make an API call using a Python SDK. SageMaker will launch ECS instances, run model training, persist the training artifacts to S3, and then shut down the EC2 instances automatically. Even in deployment, SageMaker helps automate things. Another API call will create EC2 instances and networking rules to access the model over the internet. — INTRODUCTION SageMaker is AWS’s fully managed service for building and deploying machine learning models in production. Developers can use SageMaker to label and prepare data, choose an algorithm, train, tune and optimize models, and deploy them to the cloud on scale.

AWS

4 min read

AWS: SageMaker for Machine Learning (An Amazon Web Services product)
AWS: SageMaker for Machine Learning (An Amazon Web Services product)
AWS

4 min read


Dec 8, 2022

AWS for Deep Learning — Terms to explore

S3, EFS, EC2, SageMaker, DLAMI etc — With cloud deep learning, you can request as many GPU machines as needed, and scale up and down on demand. Amazon Web Services (AWS) provides an extensive ecosystem of services to support deep learning applications like SageMaker and Deep Learning Containers. Any deep learning project requires three essential resources —…

Amazon Web Services

3 min read

AWS for Deep Learning — Terms to explore
AWS for Deep Learning — Terms to explore
Amazon Web Services

3 min read


Dec 6, 2022

Computer Vision: Non-Max Suppression (Object Detection)

A bounding box is a rectangle around an object that specifies its location in the image, its class and a probability metric of confidence describing how likely the object is within that box. We either use the corner points (x1, y1, x2, y2) or length dimensions along with the center…

Computer Vision

3 min read

Computer Vision: Non-Max Suppression (Object Detection)
Computer Vision: Non-Max Suppression (Object Detection)
Computer Vision

3 min read


Dec 4, 2022

Machine Learning: Notes on Overfitting

A model is an overfit when it has learned certain unique features of the training data, but not enough general ones to perform well on unseen data. It is thus not ready for real-world use. Causes: If a model has high variance and low bias, its training accuracy increases, but validation…

Overfitting

2 min read

Machine Learning: Notes on Overfitting
Machine Learning: Notes on Overfitting
Overfitting

2 min read


Dec 3, 2022

Big Data: Data Warehouse and Data Lake

The term ‘big data’ implies an enormous amount and variety of structured and unstructured data that needs to be processed and updated at very high speeds. Data Warehouse A data warehouse facilitates the storage of structured and semi-structured data from various sources, both historical and current, that allows decision-makers to extract insights…

Big Data

2 min read

Big Data: Data Warehouse and Data Lake
Big Data: Data Warehouse and Data Lake
Big Data

2 min read


Dec 1, 2022

Deep Learning: Guidelines for model optimization and tuning

a rough outline — A neural network model is represented by a set of parameters and hyperparameters. The parameters include the weights and biases of all nodes, and the hyper-parameters include a number of levers like layers, nodes in a layer, activation functions, cost functions, learning rate, and optimizers. Training neural model means determining…

Deep Learning

10 min read

Deep Learning: Guidelines for model optimization and tuning
Deep Learning: Guidelines for model optimization and tuning
Deep Learning

10 min read


Dec 1, 2022

Deep learning: A non-mathematical intuition of how a neural network learns

First, we make the data conducive to computers — that is, we convert it into vectors and matrices. The data also needs to be organized as samples and features. Then we split it into training, validation, and test sets. …

Deep Learning

5 min read

Deep learning: A non-mathematical intuition of how a neural network learns
Deep learning: A non-mathematical intuition of how a neural network learns
Deep Learning

5 min read

Aaweg-I

Aaweg-I

387 Followers

We put ghosts in machines.

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