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Publisher ‏ : ‎ Springer; 1st ed. 2024 edition (January 3, 2024)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 473 pages
ISBN-10 ‏ : ‎ 3031469895
ISBN-13 ‏ : ‎ 978-3031469893
Item Weight ‏ : ‎ 1.85 pounds
Dimensions ‏ : ‎ 6.5 x 1.25 x 9.5 inches

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Are you an engineer looking to dive into the world of machine learning? Look no further! In this crash course, we’ll cover the basics of machine learning, including key concepts, algorithms, and tools that every engineer should know.

1. Introduction to Machine Learning
– What is machine learning?
– Types of machine learning (supervised, unsupervised, reinforcement learning)
– Why is machine learning important for engineers?

2. Key Concepts
– Data preprocessing (cleaning, normalization, feature engineering)
– Model training and evaluation
– Overfitting and underfitting
– Bias-variance tradeoff

3. Popular Algorithms
– Linear regression
– Logistic regression
– Decision trees
– Random forests
– Support vector machines
– Neural networks

4. Tools and Libraries
– Python and its libraries (NumPy, pandas, scikit-learn)
– TensorFlow and Keras for deep learning
– Jupyter notebooks for interactive coding

5. Hands-On Project
– Apply what you’ve learned to a real-world dataset
– Build and train a machine learning model
– Evaluate the model’s performance and make improvements

By the end of this crash course, you’ll have a solid understanding of machine learning principles and be ready to tackle more advanced topics. So grab your laptop and let’s get started on this exciting journey into the world of machine learning!
#Machine #Learning #Crash #Engineers