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machine learning

Machine Learning

₹12,999.00

Machine learning is a process of teaching computers to learn from data, without being explicitly programmed. Machine learning is a subset of artificial intelligence (AI).

Machine learning algorithms build models based on sample data, known as “training data“, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision.

There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.

Supervised learning algorithms are used to train models on training data so that they can make predictions or decisions. Unsupervised learning algorithms are used to train models on data where the target values are not known. Reinforcement learning algorithms are used to train models so that they can make decisions in environments where the consequences of their actions are not known in advance.

 

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Description

New batch starting:
Date: 16-06-2023
Duration per session: 120 mins
Course Duration: 15 days
Training Platform: Online

 

The curriculum of machine learning can be divided into five main parts:

1. Data Preprocessing: The first part of the curriculum is focused on preprocessing the data. This includes cleaning the data, dealing with missing values, and scaling the data.

2. Model Selection: The second part of the curriculum is focused on model selection. This includes choosing the right model for the data, tuning the model, and evaluating the model.

3. Model Training: The third part of the curriculum is focused on training the model. This includes using different techniques to train the model, such as supervised learning, unsupervised learning, and reinforcement learning.

4. Model Evaluation: The fourth part of the curriculum is focused on evaluation the trained model. This includes using different metrics to evaluate the model, such as accuracy, precision, recall, and F1 score.

5. Model Deployment: The fifth part of the curriculum is focused on deployment of the trained model. This includes using different techniques to deploy the model, such as web services, desktop applications, and mobile applications.

 

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