Joselin Nino’s Post

𝗗𝗔𝗬 𝟭𝟲: 𝗔𝗭𝗨𝗥𝗘 𝗔𝗜 𝗦𝗘𝗥𝗩𝗜𝗖𝗘𝗦 - 𝗢𝗕𝗝𝗘𝗖𝗧 𝗗𝗘𝗧𝗘𝗖𝗧𝗜𝗢𝗡! Object detection goes a step beyond image classification by identifying and locating objects within an image. Azure AI Services make this process intuitive, enabling developers to create powerful solutions with ease. Today, I explored Azure Custom Vision for object detection and successfully built a model capable of detecting objects in images. Here's what I achieved: 𝟭. 𝗦𝗘𝗧𝗧𝗜𝗡𝗚 𝗨𝗣 𝗔 𝗖𝗨𝗦𝗧𝗢𝗠 𝗩𝗜𝗦𝗜𝗢𝗡 𝗣𝗥𝗢𝗝𝗘𝗖𝗧 Created an object detection project, chose bounding-box labeling, and prepared the environment for training. 𝟮. 𝗨𝗣𝗟𝗢𝗔𝗗𝗜𝗡𝗚 𝗔𝗡𝗗 𝗟𝗔𝗕𝗘𝗟𝗜𝗡𝗚 𝗗𝗔𝗧𝗔 Added training images for objects like apples, bananas, and oranges, carefully labeling the objects with bounding boxes. 𝟯. 𝗧𝗥𝗔𝗜𝗡𝗜𝗡𝗚 𝗧𝗛𝗘 𝗠𝗢𝗗𝗘𝗟 Trained the model to detect and differentiate between multiple objects in an image with high accuracy. 𝟰. 𝗧𝗘𝗦𝗧𝗜𝗡𝗚 𝗧𝗛𝗘 𝗠𝗢𝗗𝗘𝗟 Tested the model with real-world images and observed its impressive performance in identifying objects and their locations. A big shoutout to my mentors Krishnaa Saravanan, Suganraj S, and Dorene Roxana, and the incredible support from Microsoft Learn Students Community St.Joseph's Group Of Institutions,PEP Cloud Computing (AWS/ Azure/ GCP) and DevOps Centre for making this journey so enriching! 𝗦𝘁𝗲𝗽-𝗯𝘆-𝘀𝘁𝗲𝗽 𝗴𝘂𝗶𝗱𝗲: https://lnkd.in/gWMgKJ_z 𝗗𝗮𝗶𝗹𝘆 𝗣𝗢𝗖 𝘂𝗽𝗱𝗮𝘁𝗲𝘀: https://lnkd.in/ggwzGPrF Excited to take these learnings further and apply them to impactful real-world solutions! #AzureAI #ObjectDetection #CustomVision #MachineLearning #30DaysOfAzure #AI

🎉 Excited to share my latest learning milestone! As part of the Gen AI Campaign organized by GDG on Campus XIE, I had the chance to dive into the world of Google Cloud and Generative AI. This experience allowed me to explore practical applications of cutting-edge tools and technologies, leading to certifications in topics like: 🔹 Google Cloud Compute Basics 🔹 Cloud Storage Essentials 🔹 API Gateway Fundamentals 🔹 Google Workspace Tools 🔹 Exploring App Engine: 3 Ways 🔹 Introduction to Generative AI 🔹 Cloud Speech API: 3 Approaches 🔹 Dataplex and Data Management 🔹 Networking on Google Cloud 🔹 Cloud Vision API for Image Analysis 🔹 Pub/Sub Messaging System 🔹 Insights with Looker 🔹 Building GenAI Apps with Gemini & Streamlit 🔹 Designing Prompts in Vertex AI 🔹 Monitoring and Cloud Functions This journey has expanded my perspective on how these tools can solve real-world problems, and I’m eager to apply this knowledge to future projects. #GoogleCloud #GenerativeAI #GDGonCampus #LearningJourney #XIE #Certifications #AI #CloudComputing

The demand for ML expertise is skyrocketing, but not everyone has the time to become a coding guru. That's where AutoML comes in. AutoML platforms empower users of all skill levels to build and deploy powerful ML models, democratizing access to this game-changing technology. Two leading platforms worth exploring: - Google AutoML: Leverages Google's AI power to deliver high-quality models with a user-friendly interface. ✅ Pros: Easy to use, highly customizable, seamlessly integrated with Google Cloud. ❌ Cons: Can be expensive at scale, offers less control for experienced data scientists. - DataRobot: Automates virtually the entire ML pipeline, from data prep to deployment. ✅ Pros: Handles the heavy lifting, offers a wide range of models, ideal for enterprise-scale projects. ❌ Cons: Can be overwhelming for beginners, requires a significant investment. You can go to this web to see more details: https://buff.ly/4e0OoX9 Do you use any other platform? tell me in the comments! #MachineLearning #AutoML #DataScience

☁️🚀 DeepSeek R1 is Now on Azure AI Foundry & GitHub! 🤖💡 Great news for AI developers and enterprises! DeepSeek R1 is now available in the Azure AI Foundry model catalog and on GitHub, joining a growing portfolio of 1,800+ AI models—including frontier, open-source, industry-specific, and task-based AI models. 🔹 Why does this matter? DeepSeek R1 offers a powerful, cost-efficient AI model that helps businesses integrate advanced AI seamlessly and securely while meeting SLAs, security, and responsible AI commitments—all backed by Microsoft’s trusted cloud. ⚡ Accelerate AI Innovation with Azure AI Foundry With built-in model evaluation tools, developers can experiment, benchmark, and scale AI-powered applications faster than ever. This rapid accessibility enables businesses to unlock new opportunities with minimal infrastructure investment. 🛡️ Develop AI with Trust & Security DeepSeek R1 has undergone rigorous safety evaluations, red teaming, and automated assessments to ensure secure and responsible AI deployment. With Azure AI Content Safety, enterprises can confidently build AI solutions in a compliant and secure environment. 🔗 How to Get Started with DeepSeek R1 ✅ On Azure AI Foundry: 1️⃣ Sign up for an Azure account if you don’t have one. 2️⃣ Search for DeepSeek R1 in the model catalog. 3️⃣ Open the model card and click Deploy to access the inference API & playground. 4️⃣ Start testing your prompts in less than a minute! ✅ On GitHub: Explore resources, guides, and integration steps to seamlessly deploy DeepSeek R1 in your applications. 💻 What’s Next? Coming soon, distilled versions of DeepSeek R1 will be available to run locally on Copilot+ PCs—bringing advanced AI reasoning to more devices than ever. 🚀 Get started today! Try DeepSeek R1 on Azure AI Foundry and GitHub and unlock new AI-powered possibilities. 🔗 Start here: https://lnkd.in/efywSsVq #AzureAI #AIInnovation #DeepSeek #MachineLearning #ResponsibleAI

Thrilled to share that I've just earned the 𝗚𝗲𝗺𝗶𝗻𝗶 𝗳𝗼𝗿 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗯𝗮𝗱𝗴𝗲 𝗳𝗿𝗼𝗺 Google Cloud! 🚀 This journey has been incredibly insightful, diving deep into how Gemini is revolutionizing the way we build applications. For all my fellow developers and tech enthusiasts, understanding and leveraging AI like Gemini is becoming crucial to stay ahead. Here’s a glimpse of what I've learned and how it can add value to your work: 𝗕𝗼𝗼𝘀𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗦𝗽𝗲𝗲𝗱: Gemini’s AI-powered features can significantly accelerate your coding process, helping you bring ideas to life faster. 𝗕𝘂𝗶𝗹𝗱 𝗦𝗺𝗮𝗿𝘁𝗲𝗿 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: Integrate cutting-edge AI capabilities into your apps to create more intelligent and user-centric experiences. 𝗨𝗻𝗹𝗼𝗰𝗸 𝗡𝗲𝘄 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻: Explore the potential of generative AI to solve complex problems and build innovative solutions you might not have thought possible before. Eager to explore how Gemini and Google Cloud can further empower application development! Let's connect and discuss how AI is shaping the future of tech. Badge Link: https://lnkd.in/dvugVm7A 𝗔𝗿𝗲 𝘆𝗼𝘂 𝗲𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴 𝗔𝗜 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄? 𝗜'𝗱 𝗹𝗼𝘃𝗲 𝘁𝗼 𝗵𝗲𝗮𝗿 𝘆𝗼𝘂𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝘀 𝗮𝗻𝗱 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀 𝗯𝗲𝗹𝗼𝘄! 👇 #GoogleCloud #Gemini #ApplicationDevelopment #AI #ArtificialIntelligence #Developers #CloudComputing #Innovation #Tech

Hello LInks!!! 🚀 𝐃𝐚𝐲 [20] 𝐨𝐟 𝐦𝐲 𝐀𝐖𝐒 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐀𝐖𝐒 𝐑𝐞𝐤𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧! Today, I dived into Amazon Rekognition and explored its Label Detection, Facial Analysis, Celebrity Recognition, and Video Analysis features! Here’s how each feature works and what steps I followed to implement them: 1.𝐋𝐚𝐛𝐞𝐥 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧: Rekognition automatically identifies objects, scenes, and concepts in images, from simple items to complex scenarios. Steps: I uploaded sample images to an S3 bucket and used Rekognition’s API to analyze and tag elements like cars, animals, trees, and more. 2.𝐅𝐚𝐜𝐢𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Rekognition can detect attributes such as age range, emotions, and specific facial landmarks, enabling personalized insights. Steps: I processed various images to retrieve emotion detection, age estimation, and landmark details, observing how Rekognition identifies facial attributes. 3.𝐂𝐞𝐥𝐞𝐛𝐫𝐢𝐭𝐲 𝐑𝐞𝐤𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧: This feature identifies celebrities in images, particularly useful in media, entertainment, and marketing. Steps: I tested Rekognition on images with well-known figures, observing its ability to recognize public figures accurately. 4.𝐕𝐢𝐝𝐞𝐨 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Frame-by-frame video analysis detects scenes, actions, and objects, which is essential for content moderation and contextual advertising. Steps: I uploaded a sample video and used Rekognition to analyze each frame, identifying objects and actions throughout the video. 5.Word detection: Finally, I ran word detection on images containing text (such as signs and documents) and saw Rekognition accurately detect and extract words. This feature is ideal for digitizing text from visual sources, making unstructured content accessible and searchable. 📝 A huge thanks to my mentors Dhanish Ahmed and Soundariya B for guiding me through this journey, providing invaluable insights along the way! 🙏 PEP Cloud Computing (AWS/ Azure/ GCP) and DevOps Centre and AWS Cloud Club St.Joseph's Group of Institutions #AmazonRekognition #AWS #CloudComputing #MachineLearning #AI #30DaysCloudChallenge #Day20 #LearningEveryday #Innovation #30DaysAWSCloudChallenge

🚀 Project 3:4 Saving User Information with BankerBot Complete! 🤖 Today’s progress highlights: 💾 Stored User Information: Successfully used an output context tag to save user birthdays, reducing repetitive questions. 💬 Set Up FollowupCheckBalance Intent: Created an intent to handle balance inquiries without re-asking for the birthday. 🔄 Enabled Context Carryover: Implemented context carryover to reuse user info smoothly in subsequent interactions. Excited about how these enhancements improve user experience! #AWS #AmazonLex #ChatbotDevelopment #LearningJourney #AI #CloudComputing Natasha Ong NextWork Amazon Web Services (AWS)

Leveled up my Google Cloud skills with these badges! ☁️ Excited to share that I've earned some new badges on the Google Cloud Platform! These badges validate my knowledge of using some of Google's latest generative AI and development tools. Level 3: GenAIus Registries: This badge demonstrates my understanding of managing artifacts in Artifact Registry, a key component for storing and versioning machine learning models and datasets. Develop GenAI Apps with Gemini and Streamlit: This badge proves my ability to build user interfaces for generative AI models using Gemini and Streamlit. Now I can turn powerful AI models into interactive applications! Prompt Design in Vertex AI: This badge showcases my skills in crafting effective prompts to guide generative AI models toward the desired outputs. These badges represent a significant step forward in my journey with Google Cloud's Generative AI tools. Feeling confident and excited to explore the possibilities! I can't wait to delve deeper into these technologies and build projects using these skills. I'd like to thank VALASALA RAKESH for suggesting this program and helping me throughout this! #google #promptdesign #genai #gdsc #googlecloud

🚀 Project 4: Memory on the Move! - Enhancing BankerBot with Context Carryover 🤖 I am excited to share the next step in my AI x AWS series, where I’m advancing my skills in chatbot development using Amazon Lex and AWS Lambda. In this project, I’ve added context carryover to BankerBot, enhancing its functionality. 💡 What is Context Carryover? It enables chatbots to remember user details across multiple interactions, such as account types or recent queries. This helps provide a smoother experience by using previous inputs without asking again, making conversations more efficient and personalize 👨💻 Key Skills Showcased: 1. Setting up Amazon Lex chatbot with custom intents and slots 2. AWS Lambda integration for backend processing 3. Implementing context carryover for enhanced user experience 4. Improving bot interactions with personalized and streamlined responses The hands-on experience from this project has helped me sharpen my skills in AI and cloud computing while offering a deeper understanding of building dynamic, real-world applications. 💼 If you’re interested in chatbot development or exploring AI integrations, feel free to connect! Looking forward to continuing this journey with my next project. #AI #AWS #ChatbotDevelopment #CloudComputing #AmazonLex Amazon Web Services (AWS)#Lambda #BusinessAndTechnology #AIxAWS Sand TechnologiesNextWork

GenAI is undoubtedly a major focus for many of us in the tech industry right now. Yesterday, I had the pleasure of participating in AWS's Customer Experience GenAI Roundtable. The event featured a lineup of excellent speakers who shared invaluable insights into Amazon Web Services (AWS)'s expansive GenAI ecosystem and the working methodologies at Amazon and AWS. One key takeaway for me is that while GenAI is generating significant hype among the general public, its potential impact could still be underestimated. Since AWS made Bedrock publicly available in April 2023, many companies, including us at emax digital, have been leveraging their expertise to create use case-specific GenAI tools. Now, we're seeing more and more of these focused products emerging from beta, enhancing our daily lives with productivity-boosting assistants, coaches, and entertaining tools like real-time storytellers and games. Even non-technical individuals can now explore and build prototype apps using tools like https://partyrock.aws/, making GenAI accessible to a broader audience. The future is incredibly exciting, and I'm thrilled to be part of this innovative journey! #GenAI #ArtificialIntelligence #AWS #MachineLearning #AI #DigitalTransformation #FutureOfWork #AItools #TechCommunity #AWSBedrock