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- Dive into Deep Learning with Neural Networks to solve complex data problems.
- Learn to build and optimize neural networks using frameworks like TensorFlow and Keras.
- Implement cutting-edge deep learning techniques for tasks like image recognition, NLP, and predictive modeling.
- Understand the key concepts of Supervised and Unsupervised Learning for real-world data modeling.
- Master popular algorithms like Linear Regression, Decision Trees, and K-Means Clustering.
- Build machine learning models from scratch using Python and its powerful libraries.
- Learn the core Machine Learning libraries: Numpy for numerical computation, Pandas for data manipulation, and Matplotlib for data visualization.
- Explore Scipy’s advanced mathematical functions for Machine Learning and Data Science.
- Gain practical experience by applying these libraries to data analysis and machine learning problems.
- Master Python programming from fundamentals to advanced concepts, including OOP and data structures.
- Develop skills in Python for web development, automation, and data analysis.
- Get hands-on experience with Python libraries like Numpy, Pandas, and Matplotlib for real-world applications.
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