Automatic Number Plate Recognition Using Tensorflow and EasyOCR - Python
Learn to build a real-time Automatic Number Plate Recognition system using Python, TensorFlow, and EasyOCR. Covers plate detection, OCR application, and result saving for practical implementation.
Evaluate LayoutLMv3 for Document Classification - Save & Load Model to HuggingFace Hub
Learn to evaluate LayoutLMv3 for document classification, save and load models to HuggingFace Hub, and analyze performance using confusion matrices in this hands-on tutorial.
Introduction to Machine Learning for Coders
Learn essential machine learning concepts and techniques for coders, covering fundamental principles and practical applications across 12 comprehensive lessons.
From Notebook to Kubernetes: Scaling GenAI Pipelines with ZenML
Explore a lightning talk demonstrating how ZenML, an open-source MLOps framework, facilitates the seamless transition from local development to cloud-scale deployment of generative AI pipelines. Follow a workflow that begins in a Jupyter notebook with lo…
Training Llama 2 in Julia - Scaling Large Language Models
Explore scaling techniques for training large neural networks like Llama2 using Julia, including multi-GPU parallelization and fine-tuning methods for efficient model adaptation.
Train and Deploy Models Lightning Fast
Accelerate AI innovation by mastering techniques for rapid model training and deployment, addressing scalability and security challenges in complex AI applications.
From Concept to Production: Template for the Entire ML Journey - Part 1
Develop a production-ready ML pipeline from concept to deployment using Python. Gain hands-on experience with data prep, model training, and deployment on Google Cloud Platform.
Deploying Efficient Data-Centric AI 100x Faster
Accelerate AI application development and deployment 100x using dedicated platforms, data labeling, pre-built models, and iterative design. Explore region classification and deep-trained object detection approaches.
From Concept to Production: Building a Production-Ready ML Pipeline - Part 2
Develop a production-ready ML pipeline from concept to deployment using Python, Kubeflow, and Google Cloud Platform. Master data prep, model training, and orchestration techniques.
Challenges for ML Operations in a Fast Growing Company
Explore ML operations challenges in rapidly growing companies. Learn strategies for scalable platforms, efficient model training, and balancing distributed vs. non-distributed applications. Gain insights on developer ergonomics and best practices.
Avoid ML OOps with ML Ops - A Modular Approach to Scaling End-to-End ML Platforms
Discover a step-by-step approach to building a scalable ML infrastructure. Learn to identify key areas for improvement, implement modular components, and enhance your end-to-end ML lifecycle for efficient, automated operations.
Evolution of ML Training and Serving Infrastructure at Pinterest Ads
Explore Pinterest Ads' ML infrastructure evolution, from logistic regression to transformer models, and learn key challenges and lessons in revolutionizing ad capabilities.
LLMOPS: Training a Small LLM (GPT-2) - Machine Learning and Data Science
Explore training a small LLM (GPT2) locally, understanding challenges and limitations of LLM development for individuals and small teams.
Deploying Efficient Data-Centric AI 100x Faster
Accelerate AI application development and deployment 100x using dedicated platforms, data labeling, pre-built models, and AI-automation. Explore region classification and deep-trained object detection approaches.
End-to-End MLOps for Computer Vision
Explore end-to-end MLOps for Computer Vision, from data gathering to model monitoring. Learn to implement ML pipelines using tools like Amazon SageMaker, Kubernetes, Kubeflow, and MLFlow.
Deploy High Scale ML Models Without the Hustle
Learn to build and operate production-grade ML systems, from model training to deployment and monitoring, using the Qwak platform for efficient, high-scale solutions.
Intro to MLOps: Build, Deploy, and Retrain a Model in Production
Build, deploy, and retrain a production ML model using open-source tools. Learn robust MLOps pipeline techniques for quick model deployment and continuous improvement.
MLOps is Just HPC in Disguise - A Real-World, No-Nonsense Guide to Upgrading Your Workflow
Upgrade your ML workflow with efficient tools and techniques for automating tasks, managing resources, and streamlining production deployment in this practical guide to MLOps.
Supporting Sales Forecasting at Scale for Canada's Largest Grocery Store
Explore MLOps platform setup on Google's Vertex AI for sales forecasting at Canada's largest grocery chain. Learn to track ML lifecycle stages and expedite data science projects from exploration to production.
A Guide to Building a Continuous MLOps Stack with GCP and Superwise
Dive into MLOps CI/CD pipeline automation with GCP and Superwise. Learn to build, deploy, and monitor continuous ML pipelines, focusing on automations and production-first insights for issue detection and resolution.
Transforming the Physical World with AI - Samsara's Journey in Fleet Management Technology
Explore how Samsara leverages Ray and Anyscale to revolutionize AI in fleet management. Discover the impact of AI across their entire pipeline, from training to deployment, and its transformative effects on physical operations.