Defense Against Prompt Injection Attacks in LLM-Integrated Applications
Explore effective strategies for securing LLM applications against prompt injection attacks through structured queries and specialized instruction tuning techniques.
Formation Tensorflow 2.0
Apprenez les fondamentaux de TensorFlow 2.0, des perceptrons aux réseaux de neurones récurrents, en passant par la normalisation des données et la création de modèles personnalisés.
Machine Learning and Neural Networks: Cost Function and Gradient Descent - Day 12
Explore cost functions and gradient descent in machine learning and neural networks, focusing on their role in optimizing model performance and accuracy.
Demystifying AI - Understanding Machine Learning Fundamentals
Fundierte Einführung in Künstliche Intelligenz: Grundlagen des maschinellen Lernens, mathematische Konzepte und Herausforderungen werden verständlich erklärt. Praktische Tipps für den Einstieg inklusive.
Boosting LLM Development and Training Efficiency: Automated Parallelization with MindSpore
Explore automated parallelization for efficient LLM development and training using MindSpore. Learn to optimize distributed training on large-scale clusters without intrusive model modifications, accelerating AI research and implementation.
Fine-Tuning Gemini 1.0 Pro for Text Classification in Spanish - Machine Learning and Data Science
Aprende a ajustar el modelo Gemini Pro 1.0 en Google Vertex AI para clasificación de texto, utilizando la interfaz de usuario y el SDK.
Azure ML: Python SDK v2 - Machine Learning Applications in Azure Using Python
Desarrolla aplicaciones de Machine Learning en Azure utilizando Python SDK v2. Aprende a entrenar modelos y crear soluciones de ciencia de datos eficientes.
MLOps MLflow: Fine-Tuning Mistral 7B con PEFT y QLora - Español
Aprende a ajustar Mistral 7B utilizando técnicas avanzadas como PEFT y QLora, integrando MLflow para un seguimiento eficiente del proceso de fine-tuning.
Deep Learning Workshop for Satellite Imagery - Training & Prediction
Hands-on deep learning workshop for satellite imagery, covering model training, debugging, prediction, and advanced techniques like custom metrics, heatmaps, and model deployment.
Deep Learning Workshop for Satellite Imagery - Data Processing
Hands-on workshop on data processing for satellite imagery, covering fundamentals, Python processing, image manipulation, and preparation of training data for deep learning applications.
Understanding the Legal Context of AI
Explore the legal landscape of AI, focusing on copyright issues, model training, and intellectual property concerns in machine learning-based services.
Model Training on Snowflake with Ray
Discover how to leverage Snowflake Container Runtime and Ray for efficient, scalable model training through a practical demonstration of performance optimization techniques.
Author Interview - Transformer Memory as a Differentiable Search Index
Explore a novel approach to information retrieval using a single Transformer model that encodes corpus information in its parameters, enabling direct query-to-document mapping without external indices.
Wio Terminal TinyML Course - Anomaly Detection for Predictive Maintenance with Blynk IoT Platform
Learn to implement anomaly detection for predictive maintenance using Wio Terminal, TinyML, and Blynk IoT platform. Covers data collection, model training, testing, and integration with IoT systems.
Leadership and AI
Explore the critical role of leadership in AI adoption, emphasizing the importance of understanding AI models, their applications, and potential pitfalls to drive organizational success and avoid historical missteps.
Kubeflow and Beyond - Automation of Model Training, Deployment and Testing
Automate ML workflow: data gathering, model training, deployment, testing, and production inferencing with a single command. Streamline the process for efficient continuous delivery.
What's New with Databricks Machine Learning
Explore Databricks' latest ML innovations, from data preparation to model deployment, in a detailed demo showcasing simplified lifecycle management and enhanced productivity features.
Using the Data Science Process - Lesson 5
Explore the data science process from project inception to completion, covering key steps for successful implementation in Databricks and Apache Spark projects.
Implementing End-to-End Demand Forecasting with Databricks and MLflow
Discover how to implement a scalable demand forecasting solution using Databricks and MLflow, improving retail efficiency and reducing food waste through accurate production and delivery planning.
Stock Price Prediction Using Deep Learning - Deep Learning Tutorial
Learn to predict stock prices using deep learning techniques, including time series forecasting, ANN, and RNN, with practical implementation and a case study approach.
Training and Ensuring Reliability of ML Models - The Power of ArgoCD, Flyte, and Argo Workflows
Explore Wolt's approach to reliable ML model training and deployment using ArgoCD, Flyte, and Argo Workflows. Learn strategies for scalability, consistency, and collaboration in ML operations.