This is an introductory course on machine learning. The course covers a wide range of topics, from handling a dataset to model delivery. Some prior training in Python programming and basic calculus knowledge will help you get the best out of this course.
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This course covers Python for data science and machine learning in detail and is for a beginner in Python. You will also learn about core concepts of data science, exploratory data analysis, statistical methods, role of data, challenges of bias, variance and overfitting, model evaluation techniques, model optimization using hyperparameter tuning, grid search cross-validation techniques, and more.
If you are new to Quantum computing, then this course will help you understand the fundamentals and practicalities of this field. This course will provide you with step-by-step guidance in learning the implementation and important methodologies associated with Quantum computing in a beginner-friendly environment.
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In this course, we will start with extremely basic concepts such as learning the programming language fundamentals and other supporting libraries. Then we will proceed with the core topics with the help of real-world datasets to gain a complete understanding of deep learning using Python and Keras.
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Use deep learning, Computer Vision, and machine learning techniques to build an autonomous car with Python
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Build 9 projects to master 2 essential and modern technologies: Python and PostgreSQL