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Jaime Dantas
Jaime Dantas

87 Followers

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Published in Towards Data Science

·Pinned

The importance of k-fold cross-validation for model prediction in machine learning

This article will discuss and analyze the importance of k-fold cross-validation for model prediction in machine learning using the least-squares algorithm for Empirical Risk Minimization (ERM). We’ll use a polynomial curve-fitting problem to predict the best polynomial for the sample dataset. …

Machine Learning

8 min read

The importance of k-fold cross-validation for model prediction in machine learning
The importance of k-fold cross-validation for model prediction in machine learning
Machine Learning

8 min read


Published in Towards Data Science

·Pinned

In-depth analysis of the regularized least-squares algorithm over the empirical risk minimization

This article will introduce key concepts about Regularized Loss Minimization (RLM) and Empirical Risk Minimization (ERM), and it’ll walk you through the implementation of the least-squares algorithm using MATLAB. The models obtained using RLM and ERM will then be compared and discussed against each other. We’ll use a polynomial curve-fitting…

Machine Learning

11 min read

In-depth analysis of the regularized least-squares algorithm over the empirical risk minimization
In-depth analysis of the regularized least-squares algorithm over the empirical risk minimization
Machine Learning

11 min read


Published in Reverse Engineering

·Pinned

How I created a multi-cloud distributed solution with AWS and Azure free tier

In this post, I’ll describe step-by-step how I built an entire distributed solution using only AWS and Azure free tier products. The services I created were scattered throughout both these cloud providers, and they are up and running in production mode 24/7 at this moment. These services were coded in…

Cloud Computing

9 min read

How I created a multi-cloud distributed solution with AWS and Azure free tier
How I created a multi-cloud distributed solution with AWS and Azure free tier
Cloud Computing

9 min read


Published in Reverse Engineering

·Pinned

DC Control: a robust and low-cost SNMP agent for data centers

A few years ago, I’ve created a reliable and low-cost SNMP device to monitor and control a data center environment, and on this post, I’ll walk you through the entire design process I went through, as well as all features this network equipment is capable of. …

Makers

9 min read

DC Control: a robust low-cost SNMP agent for data centers
DC Control: a robust low-cost SNMP agent for data centers
Makers

9 min read


Published in Reverse Engineering

·Pinned

The five reasons why distributed architectures powered by Kafka overpass classical software designs

Nowadays, cloud solutions are gaining popularity day after day among giant companies that once relied on on-premise infrastructures and high-performance computer architectures, also known as mainframe-based systems. This trend was first boosted by big tech companies, especially the ones defined as FAAMG companies. …

Distributed Systems

8 min read

The five reasons why distributed architectures powered by Kafka overpass classical software designs
The five reasons why distributed architectures powered by Kafka overpass classical software designs
Distributed Systems

8 min read


Mar 8

Essential concepts of Cloud Computing

Cloud computing has become a predominant IT operation platform in the past decade. Small and large companies have been migrating their workloads to the cloud, and serverless architectures, such as container and Function as a Service (FaaS), are among the popular choices for cluster software deployments. …

Cloud Computing

5 min read

Essential concepts of Cloud Computing
Essential concepts of Cloud Computing
Cloud Computing

5 min read


Published in Towards Data Science

·Aug 16, 2021

Differential privacy and k-anonymity for machine learning

User privacy is a rising concern in the nowadays data-driven world. we’ll investigate the impacts of the use of anonymization techniques on public medical-related datasets where some private information of patients is present which could allow re-identification attacks. We will evaluate a feed-forward neural network using local differential privacy with…

Differential Privacy

8 min read

Differential privacy and k-anonymity for machine learning
Differential privacy and k-anonymity for machine learning
Differential Privacy

8 min read


Published in Reverse Engineering

·Apr 7, 2021

Creating your very first microservice with Micronaut and Kotlin

You’re probably asking yourself, what a heck is Micronaut? Why not Spring Boot? If so, this is the post for you. You’re not alone! This is because these questions are often asked by many Spring programmers when first introduced to Micronaut. With that in mind, I wrote this post to…

Software Engineering

7 min read

Creating your very first microservice with Micronaut and Kotlin
Creating your very first microservice with Micronaut and Kotlin
Software Engineering

7 min read


Published in Towards Data Science

·Dec 1, 2020

Stochastic gradient descent implementation for SoftSVM

How to choose the best regularization parameter when implementing SGD for SoftSVM — This is a quick tutorial on how to implement the Stochastic Gradient Descent (SGD) optimization method for SoftSVM on MATLAB to find a linear classifier with minimal empirical loss. We’ll see how to tune our algorithm with different regularizers by analyzing the binary and hinge loss. Dataset We will use a…

Machine Learning

6 min read

Stochastic gradient descent implementation for SoftSVM
Stochastic gradient descent implementation for SoftSVM
Machine Learning

6 min read


Published in Towards Data Science

·Nov 12, 2020

Reasons why surrogate loss functions are pivotal for classification in machine learning

This post will dive deep into the concepts and theory behind hinge loss, logistic loss and binary loss for classification in machine learning. We’ll implement the perceptron algorithm on MATLAB, and see how we can select the best classifier based on the surrogate loss functions. By the end of this…

Machine Learning

8 min read

Reasons why surrogate loss functions are pivotal for classification in machine learning
Reasons why surrogate loss functions are pivotal for classification in machine learning
Machine Learning

8 min read

Jaime Dantas

Jaime Dantas

87 Followers

Computer Engineer — www.jaimedantas.com

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