Data Science Modern Deep Learning in Python Free Download. The course, “Deep Learning 2.0: Deep Neural Networks in Python,” assumes proficiency in Python, Numpy, and Matplotlib. It builds on the foundations of AI technologies and serves as a sequel to the instructor’s “Deep Learning in Python” course.
Participants should be versed in building artificial neural networks. The curriculum covers advanced backpropagation techniques, including batch and stochastic gradient descent, momentum, and adaptive learning rate methods.
Modern techniques like dropout regularization and batch normalization are explored in TensorFlow and Theano. The course also addresses various deep learning libraries like Keras, PyTorch, CNTK, and MXNet.
Practical application is demonstrated using the MNIST dataset. Emphasis is on hands-on learning, implementing models from scratch rather than relying solely on APIs.
The course highlights the importance of implementation, aligning with physicist Richard Feynman’s belief: “What I cannot create, I do not understand.” Prerequisites include knowledge of gradient descent, probability, Python coding, Numpy, and familiarity with writing a neural network.
The suggested order for course completion is outlined in the “Machine Learning and AI Prerequisite Roadmap.” The target audience includes those seeking to deepen machine learning knowledge, expand understanding of deep learning, and enhance skills in stochastic batch training, momentum, and adaptive learning rate procedures. Participants unfamiliar with backpropagation or softmax are advised to take the earlier course, “Deep Learning in Python,” first.
Data Science Modern Deep Learning in Python Download
Data Science involves extracting insights, patterns, and knowledge from structured and unstructured data. It employs statistical methods, machine learning algorithms, and domain expertise to analyze and interpret data, facilitating informed decision-making. Data Scientists use programming languages like Python and R to explore, clean, and model data, addressing complex problems across various industries.
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