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5. Practical Deep Learning: A Python-Based Introduction DESCRIPTION COPY LINK: https://pdf.bookcenterapp.com/slide/1718500742 Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects.If you&#8217vebeen curious about machine learning but didn&#8217tknow where to start, this is the book you&#8217vebeen waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further.&nbspAllyou need is basic familiarity with computer programming and high school math&#8212th book will cover the rest. After an introduction to Python, you&#8217llmove through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models&#8217performance.&nbspYou#8217ll also learn:How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector MachinesHow neural networks work and how they&#8217retrainedHow to use convolutional neural networksHow to develop a successful deep learning model from scratch&nbspYou#8217ll conduct experiments along the way, building to a final case study that incorporates everything you&#8217velearned.&nbspnbspThe perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.

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