Python Basic to Advanced

Deep Learning- Neural Networks

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.