Introduction to Machine Learning using Python. Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of Computer Programs that can change when exposed to new data.
Course Description:
Machine Learning focuses on creating algorithms to find patterns or make predictions from experimental data. The growing field of Machine Learning has a vast range of applications in different fields like Intelligent Systems, computer vision, Speech Recognition, Natural Language Processing, Robotics, finance, information retrieval, healthcare, weather prediction. Machine Learning Master’s program develops theoretical and practical fundamentals required to be at the front of progress in the next technical revolution. The enhancements completed in Machine Learning and its related disciplines will soon trace every part of technology.
Course Objective:
After completion of this course, trainee will be able to:
- Master the concept of Python Programming.
- Clearly understand the Machine Learning concept.
- Understand the concept of Deep Learning, Natural Language Processing, Graphical modelling and Reinforcement learning.
- Understand the theory underlying machine learning algorithms.
- Use machine learning to make decisions and predictions.
- Select appropriate statistical and predictive methodologies.
Pre-requisites:
A candidate should have:
- Bachelor’s/Master’s Degree in Computer Science, Statistics, Applied Math or related field.
- B.Tech/B.E. – Any Specialization.
Who should attend this training?
This training is suitable for:
- Engineers
- Software and IT professionals.
- Data Professionals.
- Data Scientists.
- Machine Learning professionals.
Prepare for Certification!
Our training and certification program gives you a solid understanding of the key topics covered in the Master program in Machine Learning. In addition to boosting your income potential, getting certified in Master Program in Machine Learning demonstrates your knowledge of the skills necessary to be an effective Machine Learning professional. The certification validates your ability to produce reliable, high-quality results with increased efficiency and consistency. At the end of this master program, you will get a chance to work on a capstone project to gain hands-on capability.
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Introduction
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- Difference between Machine learning and Artificial Intelligence Difference between M...
- Applications Applications
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Supervised and Unsupervised learning
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Parametric Methods
- Regression and Classification Regression and Class...
- Understanding Logistic Regression Understanding Logist...
- Multivariate Regression Multivariate Regress...
- Confusion Matrix in Machine Learning Confusion Matrix in ...
- Linear Regression(Python Implementation) Linear Regression(Py...
- Softmax Regression using TensorFlow Softmax Regression u...
- Linear Regression using PyTorch Linear Regression us...
- Identifying handwritten digits using Logistic Regression in PyTorch Identifying handwrit...
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Dimensionality Reduction
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Clustering
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Non-parametric Methods
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Multilayer perceptron
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Data Processing
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Misc
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