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Cloud Computing

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Amazon CodeGuru Security

2025-08-04T05:56:18+00:00

Amazon CodeGuru Security Cheat Sheet Amazon CodeGuru Security is a static application tool that leverages machine learning to identify security vulnerabilities and policy violations. It offers actionable recommendations to mitigate security risks and generates metrics to help track the security posture of your applications. Informed by years of Amazon.com and AWS security best practices, CodeGuru Security’s policies assist in building and deploying secure, high-quality applications. Features Static Code Analysis: Uses ML and automated reasoning to detect security issues in source code (e.g., injection flaws, hardcoded credentials, etc.) Repository Scanning: Scans entire repositories or specific pull requests. ML-Based Detectors: Includes OWASP [...]

Amazon CodeGuru Security2025-08-04T05:56:18+00:00

AWS Elastic Disaster Recovery

2025-08-01T09:06:05+00:00

AWS Elastic Disaster Recovery Cheat Sheet It is a fully managed service providing fast, reliable, and cost-efficient disaster recovery for physical, virtual, and cloud-based Amazon Web Services (AWS) servers. It continuously replicates block-level data from the source environment, such as on-premises infrastructure or another cloud provider, to a staging area subnet in AWS. In the event of a disaster or during a drill, AWS DRS enables the rapid launch of fully operational recovery instances in AWS, ensuring minimal downtime and data loss. Features Continuous Replication Block-level replication from on-premises or cloud to AWS. Automated Orchestration Automates failover, recovery, and failback [...]

AWS Elastic Disaster Recovery2025-08-01T09:06:05+00:00

AWS SysOps Renamed to AWS Certified CloudOps Engineer – Associate SOA-C03

2025-09-12T05:36:22+00:00

The AWS Training and Certification team recently announced a change in one of its popular Associate-level AWS certification exams. Effective September 2025, the “AWS Certified SysOps Administrator – Associate” will be called the “AWS Certified CloudOps Engineer – Associate”  to reflect evolving industry terms and the broader scope of modern cloud operations. What's New with the AWS Certified CloudOps Engineer Associate Exam? The decision to rename the existing AWS Certified SysOps Administrator Associate exam to “AWS Certified CloudOps Engineer Associate” is made to further enhance the relevance and credibility of the certification. This better highlights the skills certified professionals have [...]

AWS SysOps Renamed to AWS Certified CloudOps Engineer – Associate SOA-C032025-09-12T05:36:22+00:00

Effectively Set-Up Your Virtual Private Cloud using CloudFormation

2025-07-16T14:28:36+00:00

Hello Dojos! We're back again for another Infrastructure as Code article, focusing on AWS Native Infrastructure as Code Service, CloudFormation In my previous article, we explored the benefits of using Infrastructure as Code to ramp up your production by showing how easy it is to launch an EC2 Instance using Terraform. For this article, we will explore AWS CloudFormation and try to deploy our very own Virtual Private Cloud. Using Terraform and CloudFormation offers their benefits and advantages, which we won't tackle right now. Nevertheless, they offer the same purpose: to make provisioning much faster and reduce the risk of [...]

Effectively Set-Up Your Virtual Private Cloud using CloudFormation2025-07-16T14:28:36+00:00

AI as a Service (AIaaS) To Power Your Business Forward

2025-07-08T12:15:24+00:00

If you have a business or kind of planning to start one, you’ve prolly heard one of the most overused quotes out there: “if you’re not growing, you’re dying.” And sure, at some point, that’s true. Undeniably.  But you see, not every business has the time, resources, or skilled team to keep up with the competition. From personalized shopping experiences to smarter customer support… How? Artificial Intelligence. Just a truly intelligent, always-on key part of how modern companies operate. AI became a requirement for all businesses to stand out and be on top in the market. But are businesses really [...]

AI as a Service (AIaaS) To Power Your Business Forward2025-07-08T12:15:24+00:00

What is ROUGE Metrics – Recall-Oriented Understudy for Gisting Evaluation?

2025-07-08T11:24:28+00:00

Recall-Oriented Understudy for Gisting Evaluation (ROUGE) Cheat Sheet ROUGE is a family of metrics designed to assess the similarity between machine-generated text (candidate) and human-written reference text (ground truth) in NLP tasks like text summarization and machine translation. Measures how well generated text captures key information and structure from reference text, emphasizing recall (proportion of relevant information preserved). Score Range: 0 to 1, where higher scores indicate greater similarity between candidate and reference texts. Key Use Cases: Evaluating text summarization systems. Assessing machine translation quality. Analyzing content accuracy in generated text. Types of ROUGE Metrics ROUGE-N: Measures the overlap of [...]

What is ROUGE Metrics – Recall-Oriented Understudy for Gisting Evaluation?2025-07-08T11:24:28+00:00

What is Retrieval Augmented Generation (RAG) in Machine Learning?

2025-06-30T03:46:57+00:00

Retrieval-Augmented Generation (RAG) Cheat Sheet Retrieval-Augmented Generation (RAG) is a method that enhances large language models (LLMs) outputs by incorporating information from external, authoritative knowledge sources. Instead of relying solely on pre-trained data, RAG retrieves relevant content at inference time to ground its responses. LLMs (Large Language Models) are trained on massive datasets and use billions of parameters to perform tasks like: Question answering Language translation Text completion RAG extends LLM capabilities to domain-specific or private organizational knowledge without requiring model retraining. It provides a cost-efficient way to improve the relevance, accuracy, and utility of LLM outputs in dynamic or [...]

What is Retrieval Augmented Generation (RAG) in Machine Learning?2025-06-30T03:46:57+00:00

What is Area Under the ROC Curve (AUC) in Machine Learning?

2025-07-01T02:38:28+00:00

Area Under the ROC Curve (AUC) Cheat Sheet AUC, short for Area Under the Curve of the Receiver Operating Characteristic (ROC), is a metric that evaluates how well a model can differentiate between different classes. A performance metric primarily used for binary classification models. Ranges from 0 to 1: 1: Perfect model. 0.5: Model performs no better than random guessing. 0: Model inversely ranks positives and negatives. Accurate Outcomes True Positive (TP): The model predicted 1, which matches the actual result. True Negative (TN): The model predicted 0, and the real outcome was also 0. Misclassified Outcomes False Positive (FP): [...]

What is Area Under the ROC Curve (AUC) in Machine Learning?2025-07-01T02:38:28+00:00

What is BiLingual Evaluation Understudy (BLEU) Score for Machine Translation?

2025-06-25T01:15:03+00:00

BiLingual Evaluation Understudy (BLEU) Score Cheat Sheet BLEU (BiLingual Evaluation Understudy) is a corpus-level metric designed to automatically evaluate the quality of machine-generated text, most commonly in machine translation (MT). It compares n-gram overlap between the machine’s output and one or more human reference translations. Introduced by Papineni et al. (2002), BLEU became the first automated metric to correlate highly with human judgments in large-scale MT evaluations. It remains a widely used baseline for evaluating machine-generated text. Common Use Cases The BLEU score is widely used in natural language processing tasks that require comparing machine-generated text to human-written references. Its primary [...]

What is BiLingual Evaluation Understudy (BLEU) Score for Machine Translation?2025-06-25T01:15:03+00:00

What is RLHF – Reinforcement Learning from Human Feedback?

2025-06-24T05:52:27+00:00

What is Reinforcement Learning from Human Feedback (RLHF)? A technique to improve AI models using human feedback to guide learning. Builds on reinforcement learning, where AI learns by trial and error to achieve goals. Uses human opinions to determine good or bad outputs, enhancing traditional reward systems. How RLHF Works Data Collection: AI generates multiple outputs (e.g., answers or text snippets). Humans provide feedback by ranking or comparing outputs (e.g., which is better or more helpful). Supervised Fine-Tuning: Model is trained with human feedback to produce preferred outputs. Establishes a baseline for good responses. Building a Reward Model: Creates a [...]

What is RLHF – Reinforcement Learning from Human Feedback?2025-06-24T05:52:27+00:00

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