A Level - Syllabus of Module: A10.5-R5-Machine Learning Using Python
Introduction :
The course would cover the spectrum of data analytics, machine learning, deep
learning, natural language processing and computer vision. The student would dive
straight into data analytics and applied machine learning and deep learning algorithms.
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| A Level - Syllabus of Module: A10.5-R5-Machine Learning Using Python |
(i) Advanced Python : Overview of Python language, Programming Constructs, Data Structures like lists,
dictionaries, tuples, sequences and their manipulations. Python Functions.
Modules and Packages, Exception Handling, NumPy Library, Broadcasting and
numpy functions. Pandas Library, working with dataframes, loading csv,
manipulating dataframes, Aggregation functions, Analysis. Visualization using
matplotlib and Seaborn.
(ii)Machine Learning :
Categories of ML, Supervised, Unsupervised, Reinforcement, Semi-Supervised.
Supervised Learning Models, Regression, Classification, Naive Bayes, Support
Vector Machines, Decision Trees, K-nearest Neighbours, Ensemble Methods of
Classification, Machine Learning Evaluation Metrics, Cross Validation.
(iii) Computer Vision : Introduction to Computer Vision, Face Recognition and Detection with OpenCV,
Face Recognisers, Training data, Prediction.
(iv) Deep Learning : Artificial Neural Networks and Model, ANN structure, Feed Forward Neural
network, Back Propagation, Deep Learning Concepts, Convolution Neural Network
(CNN), Neural Network using TensorFlow.
Learning Algorithms, Error correction and Gradient Descent Rules, Perceptron
Learning Algorithm.
(v) Natural Language Processing : Basics of text processing, Lexical processing, NLP tasks in syntax, semantics, and
pragmatics. Applications like Automatic Summarization, Sentiment Analysis and
Text Classification.
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