About the Program
Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence. Lot of opportunities is out there in field of ml and AI in India. People already using ml in field of image processing, pattern analysis, marketing, data analysis having pretty good future in India. The Machine Learning workshop provides the participants technical training on the concepts and Machine Learning algorithms to develop the code. Participants will also learn to use different Python libraries. Instruction cum aided with live projects which will allow students to grasp concepts of the complete machine learning development life-cycle.
Technologies and Tools Covered
- ANACONDA NAVIGATOR
- PYTHON PROGRAMMING LANGUAGE
- PYTHON PACKAGES/ LIBRARIES
- MACHINE LEARNING ALGORITHMS
LEARNING PATH
- MACHINE LEARNING PROCESS AND TYPES OF LEARNING
Introduction to the Concept of Machine Learning, participants come to the machine learning process and know the types of machine Learnings with suitable examples.
SESSION |
CLASS TOPICS |
1 | Introduction to Machine Learning |
2 | Overview of Machine Learning |
3 | Real time uses of machine learning |
4 | Machine learning process |
5 | Supervised learning with example |
6 | Unsupervised learning with example |
- Python Programming
Python a Powerful language and user friendly and its mostly used for most of the applications like Machine Learning, Deep Learning, Internet of Things, Block Chain. This session helps the participants to completely work on Python Programming and python libraries/ packages which are mainly used in the machine learning.
SESSION |
CLASS TOPICS |
1 | Basics of python programming |
2 | Pandas library |
3 | NumPy library |
4 | Matplotlib library |
5 | Seaborn library |
6 | Sklearn library |
- Machine Learning Algorithms
Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to do so.
SESSION |
CLASS TOPICS |
||
1 | Decision Tree classifier, Support vector machine classifier | ||
2 | Random forest classifier, Logistic Regression classifier | ||
3 | Working with Unlabeled Data (Unsupervised Learning) | ||
4 | Usage Unstructured data Predicting Elbow Method and K -means Algorithm | ||
Projects & Assignments
Practical 1: Data collection.
Practical 2: Data analysis.
Practical 3: Use of python libraries
Practical 4: Use of algorithms
Practical 5: how to predict the result
Training Methodology
The Program is mix of Theory sessions, Quizzes, Hands on Sessions, Liver Interaction with Experts, Assignments and Practical Exercises. Maximum Impetus is given to Hands on Sessions so as to enable the participants with the maximum knowledge transfer and satisfaction. The ratio of the theory, practical sessions will be 30:70.
Pantech eLearning
Agile Project Expert
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I am interested in knowing about machine learning- Deep learning
when it started?
please provide certificate
very good and informative
Wish to learn the machine learning concepts and Python