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Master Deep Learning Algorithms Using Python. Learn how to use Python to implement deep learning algorithms along with mathematical concepts as you progress from beginner to master level
Instructor: Packt - Course Instructors
Included with
Recommended experience
Beginner level
This course is helpful for Python beginners, analytics professionals, and those transitioning to data science roles with deep learning technologies.
Recommended experience
Beginner level
This course is helpful for Python beginners, analytics professionals, and those transitioning to data science roles with deep learning technologies.
Understand the principles and functioning of various deep learning architectures and algorithms.
Implement neural networks using TensorFlow and Keras for various tasks such as image classification and natural language processing.
Evaluate the performance of different neural network models and identify the factors influencing their accuracy and efficiency.
Design and develop comprehensive deep learning projects, integrating multiple techniques and tools to address complex AI challenges.
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September 2024
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Embark on an immersive journey into deep learning, where theoretical concepts meet practical applications. This course begins with a foundational understanding of perceptrons and neural networks, gradually advancing to complex topics such as backpropagation and convolutional neural networks (CNNs). Each module is meticulously designed to provide hands-on experience, allowing you to apply what you've learned to real-world scenarios.
Our curriculum emphasizes the practical aspects of deep learning, ensuring you gain valuable skills in building and training neural networks. You'll explore cutting-edge techniques and tools like TensorFlow and Keras, essential for modern AI development. From working with image data to implementing transfer learning, the course covers a broad spectrum of applications, including medical image analysis and natural image classification.
By the end of this course, you'll have a robust portfolio of projects showcasing your expertise in deep learning. You'll be equipped to tackle complex problems, optimize neural networks, and deploy models in real-world environments. Whether you're looking to advance your career in AI or start your journey in data science, this course provides the comprehensive knowledge and practical experience you need.
Ideal for data scientists, and ML engineers, with a basic understanding of Python programming and mathematics, including linear algebra and calculus. Familiarity with ML algorithms is recommended.
Applied Learning Project
The included projects are designed to solve authentic problems by applying deep learning techniques to real-world datasets. Learners will engage with practical applications such as analyzing natural images, diagnosing medical conditions using X-ray images, and implementing advanced recurrent neural network models for tasks like text generation and part-of-speech tagging. These projects ensure that learners not only understand theoretical concepts but also gain hands-on experience, enabling them to apply their deep learning skills effectively in real-life scenarios.
Run Python programs for tasks using numeric operations, control structures, and functions.
Analyze data with NumPy and Pandas for comprehensive data insights.
Evaluate the performance of linear regression and KNN classification models.
Develop optimized machine learning models using gradient descent.
Understand the concepts of perceptrons and multi-layer neural networks.
Apply training techniques, including backpropagation and regularization.
Analyze convolutional neural networks for image and video analysis.
Evaluate and create deep learning projects using frameworks like TensorFlow and Keras.
Apply transfer learning techniques to enhance model performance.
Utilize RNNs and LSTMs for sequence prediction tasks.
Develop practical solutions for industry-specific problems.
Master the integration of advanced neural networks in real-world applications.
Packt helps tech professionals put software to work by distilling and sharing the working knowledge of their peers. Packt is an established global technical learning content provider, founded in Birmingham, UK, with over twenty years of experience delivering premium, rich content from groundbreaking authors on a wide range of emerging and popular technologies.
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This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
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