Cypho’s Post

Exciting improvements to #GaleDigitalScholarLab recently released: ✅Improved text colours and mark-up view for Named Entity Recognition ✅Enabling the user to download either the top 100 or top 25 results for Ngrams ✅A tool tip to better explain Sentiment Analysis functionality

Ever heard 'Show me your friends, and I'll show you who you are'? 🌟 Discover how the #KNN algorithm uses the K-nearest points to classify new data points. Dive into more details in the image! 📊 #DataScience #MachineLearning

Phase 8: Machine Learning Model Refinement 🔒 By IIIRuS_Q – AI-Powered Network Threat Detection System (ANTDS) In Phase 8, ANTDS refines its Machine Learning (ML) models to improve detection accuracy and adapt to emerging threats. 📊 Key Features of Phase 8 1️⃣ Feedback Loops: Use SOAR results to retrain models with verified incidents. 2️⃣ Hybrid Models: Combine unsupervised (Isolation Forest) and supervised (Random Forest) approaches. 3️⃣ Feature Optimization: Extract insights like protocol patterns and traffic baselines for better classification. 4️⃣ Threat Adaptation: Enable real-time model updates to handle evolving threats. 🌐 Learn More Here: 🔗 Website: https://lnkd.in/dFGBSWu2 🔗 Connect with Me on LinkedIn: https://lnkd.in/d_2tQ6mk 🛡️ Together, we refine. Together, we defend. 🚀

#ICYMI Gale Digital Scholar Lab Parts of Speech and Sentiment Analysis tools have a new view that shows which words have been identified by the tool, and where they appear in the text, increasing transparency and helping users better understand the tool! >>https://lnkd.in/e5e6QsBx #DigitalHumanities #GaleDSLab #ProductUpdate

Unveiling the Untold Power of Proximity with K-Nearest Neighbors (KNN) Algorithm!🚀 In the realm of machine learning, behold the awe-inspiring might of K-Nearest Neighbors (KNN). Discover how this algorithm harnesses the notion that similar entities cluster together, paving the way for accurate classifications and uncanny predictions that put even the most intricate algorithms to shame! The Marvelous K-NN Magic ✨ Dive into the world of simplicity and elegance with KNN, a non-parametric wonder that thrives on proximity and the mystical 'K' factor. Whether it's classifying data or predicting outcomes, KNN's reliance on nearness guarantees its spot as a go-to technique, transcending complexities with ease. Unraveling the Enigma: KNN Unleashed 🧠 Step into the essence of KNN, where intuition meets effectiveness in a harmonious dance of classification and regression prowess. Explore how KNN's knack for neighborly camaraderie unlocks patterns and prophecies, revolutionizing domains from intrusion detection to bespoke recommendation systems. KNN: Where Simplicity Reigns Supreme 🏆 Witness firsthand how KNN upholds the fundamental belief that by understanding the known, we conquer the unknown. Through the lens of k neighbors and adaptability, KNN emerges as a beacon of reliability, ushering in a new era of predictive precision in the vast landscape of machine learning. Tracing the Legacy: Origins of KNN 🕰️ Journey through time as we unravel the historical tapestry of KNN, a beacon of light in the early days of machine learning. Explore how simplicity and proximity converged to birth an algorithmic marvel that continues to captivate minds and reshape the data science landscape. Don't miss out on the enchanting saga of K-Nearest Neighbors (KNN) - where the power of proximity reigns supreme! #MachineLearning #DataScience #KNNPowerhouse Remember, the future lies within reach - just a 'K' away! 😉

Building the cybernetic framework for a self aware synthetic intelligence. One of a series of conversations exploring and helping to shape the emergence of general synthetic intelligence. We're getting close to cracking it.

The Sysdig 2024 Global Threat Report highlights a rise in LLMjacking incidents and the evolving tactics behind them. 📈 💰 The financial impact is alarming, surpassing $100k daily, making LLMjacking a significant resource-jacking threat for organizations. Ensure your organization stays proactive — uncover strategies to address this expensive risk and safeguard your enterprise AI by exploring the latest findings from Sysdig TRT on LLMjacking. 👉 https://okt.to/dugnoO

Series Bs are heating up, while Series Cs remain in deep freeze. Our algos are dynamic - we rank each round relative to similar rounds in 90 day windows. This allows us to create thresholds to identify the top ranked rounds. This chart shows how Series B threshold scores are picking up while Series C threshold scores are flat. Visit signalrank.ai for these charts & more venture data.

Open-source intelligence (#OSINT) is a critical part of any due diligence investigation. But it comes with challenges. It’s big, hard to work with and often messy. Thankfully, there is a solution: https://hubs.li/Q02yY5wf0 In this blog post, #DataVisualization expert Dan Williams shows how to create beautiful and intuitive UI for investigations. Working with data from ShadowDragon's SocialNet API, he creates visually engaging and insightful reports that help investigators navigate information from potentially hundreds of OSINT sources. #KYC #DueDiligence

🎉 Solved the "Ceil in BST" Problem! 🎉 I recently tackled the "Ceil in BST" problem, a classic challenge in binary search trees (BSTs). The goal is to find the smallest element in the BST that is greater than or equal to a given key. Approach: Start at the root and compare the key with the current node's value. Traverse: If the node's value is less than the key, move right. If it's greater or equal, update the ceil value and move left. Repeat until you find the ceil or traverse the entire tree. This problem was a great way to reinforce my understanding of BSTs and sharpen my problem-solving skills. #BinarySearchTree #Algorithms #ProblemSolving #LearningJourney #Tech