Machine Learning Bookcamp: Build a Portfolio of Real-Life Projects - Tapa blanda

Sinopsis

The only way to learn is to practice! In   Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you’ve learned in previous chapters. By the end of the bookcamp, you’ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that’s exactly what you’ll be doing in   Machine Learning Bookcamp. about the bookIn   Machine Learning Bookcamp  you’ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you’ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You’ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you’re done working through these fun and informative projects, you’ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems.   what's inside

• Code fundamental ML algorithms from scratch
• Collect and clean data for training models
• Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow
• Apply ML to complex datasets with images and text
• Deploy ML models to a production-ready environment

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