End to End Deep Learning Project Using MLOPS DVC Pipeline With Deployments Azure and AWS - Krish Naik
Comprehensive guide to building and deploying a deep learning project for chicken disease classification using MLOps tools, DVC pipeline, and cloud platforms Azure and AWS.
End to End NLP Project Implementation With Deployment Github Action - Text Summarization - Krish Naik
Comprehensive guide to implementing an end-to-end NLP text summarization project, covering data processing, model training, evaluation, and deployment using GitHub Actions on AWS.
Deploying and Exploring QuestDB on Kubernetes - Tutorial
Explore QuestDB deployment on Kubernetes, learn its features, and witness its impressive querying capabilities on large datasets. Hands-on demonstration with expert insights.
End to End ML Project - Data Transformation Implementation Using Pipelines
Implement data transformation using pipelines for ML projects, covering categorical and missing value handling, standard scaling, and artifact storage.
Build Your Machine Learning Pipeline in These 4 Simple Steps - Loan Prediction Scikit-Learn Example
Aprenda a construir um pipeline completo de machine learning usando scikit-learn para previsão de empréstimos, desde a ingestão de dados até o uso do modelo salvo para previsões.
Ingesting 6.5 TB of Telemetry Data Daily Through Open Telemetry Protocol and Collectors
Learn how VTEX implemented Open Telemetry to handle 6.5TB of daily telemetry data, modernizing their observability stack while reducing costs and improving efficiency.
Vector Search and State-of-the-Art Retrieval for Generative AI Apps
Explore vector search, hybrid search, and reranking models for improved knowledge retrieval in Generative AI apps. Includes live code demos and evaluation insights on retrieval quality.
End-to-End Deep Learning Project: Kidney Disease Classification with MLflow, DVC, and Deployment
Comprehensive deep learning project on kidney disease classification, covering data ingestion, model preparation, training, evaluation, MLflow integration, DVC pipeline, and AWS deployment.
Optimizing Speed and Scale of Real-Time Analytics Using Apache Pulsar and Apache Pinot
Explore Apache Pulsar and Apache Pinot's synergy for high-speed, scalable real-time analytics in Cloud Native environments. Learn how these powerful tools enable efficient event streaming and ad-hoc data analysis.
Building a Security Platform with Elastic Stack - Part 1
Learn to build a security platform using Elastic Stack. Explore basic components, data ingestion tools, data management, and cluster security. Gain insights from an experienced developer on leveraging SIEM for effective security monitoring.
Why We Built Our Own Distributed Column Store
Explore the architecture and implementation of Retriever, a custom-built distributed column store database inspired by Facebook's Scuba, designed for efficient querying of large-scale event data.
Operating Elasticsearch with Ease at Scale
Discover strategies for operating Elasticsearch at scale, covering common issues, optimization techniques, and best practices for handling massive deployments with billions of ingests and millions of searches daily.
Can You Roll Your Own SIEM
Explore building a custom cloud-native SIEM solution, discussing considerations, requirements, and benefits compared to vendor options. Learn about cost savings and improved capabilities.
An Offensive Approach to Analyzing Huge and Complex Big Data Infrastructures
Explore attack vectors in Big Data stack layers: ingestion, storage, processing, and access. Learn methodologies to identify vulnerabilities in complex infrastructures handling massive data volumes.
Machine Learning with TensorFlow and Google Cloud
Explore TensorFlow and Google Cloud for machine learning applications through a hands-on example, covering data ingestion, neural network training, and prediction on real datasets.
Scaling Machine Learning with Spark
Learn to build scalable machine learning solutions with Apache Spark. Explore distributed computing, MLflow, feature engineering, and integrating Spark with deep learning frameworks like TensorFlow and PyTorch.
Enable Real-time Analytics and Machine Learning with Azure Stream
Explore Azure Stream Analytics for real-time data processing, integrating with Power BI dashboards and Azure ML. Learn to build streaming jobs and implement lambda architecture for data-driven insights.
Building a Telegram Bot with Apache Kafka, Go & ksqlDB
Hands-on demonstration of building a Telegram bot using Apache Kafka, Go, and ksqlDB for real-time data processing and querying, showcasing event-driven architecture and stream processing capabilities.
Garbage in Garbage Out - Generating Useful Log Data in Complex Environments
Explore effective log data generation in complex environments, focusing on meaningful data, thresholds, and log management systems for improved security and analysis.
Hyperconvergence Meets BigData
Explore deploying Wendelin, a Big Data & Machine Learning platform, using SlapOS, a hyperconverged OS. Learn to create and manage a complete Big Data infrastructure with Python-based tools.
NLPeasy - A Workflow to Analyse, Enrich, and Explore Textual Data
Discover NLPeasy: a streamlined workflow for analyzing, enriching, and exploring textual data using pre-trained models, Docker, and Jupyter Notebooks. Simplify your NLP projects with this powerful Python package.