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Machine Learning Workflow

This Presentation will help you in getting information about how to get start any machine learning program or any machine learning algorithms and what are the steps for i.e. how you should proceed with any machine learning algorithm

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Machine Learning Workflow

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  1. Machine Learning Workflow Powered by CETPA Infotech D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  2. Machine Learning ? Machine learning (ML) is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output while updating outputs as new data becomes available.The processes involved in machine learning are similar to that of data mining and predictive modeling. Both require searching through data to look for patterns and adjusting program actions accordingly. D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  3. Machine Learning Workflow We can define the machine learning workflow in 3 stages. • Gathering data • Data pre-processing • Researching the model that will be best for the type of data • Training and testing the model • Evaluation D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  4. Gathering Data The process of gathering data depends on the type of project we desire to make, if we want to make an ML project that uses real-time data, then we can build an IoT system that using different sensors data. The data set can be collected from various sources such as a file, database, sensor and many other such sources but the collected data cannot be used directly for performing the analysis process as there might be a lot of missing data, extremely large values, unorganized text data or noisy data. Therefore, to solve this problem Data Preparation is done.

  5. Data preprocessing is one of the most important steps in machine learning. It is the most important step that helps in building machine learning models more accurately. In machine learning, there is an 80/20 rule. Every data scientist should spend 80% time for data pre-processing and 20% time to actually perform the analysis. Data Pre-Processing D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  6. Researching the model that will be best for the type of data Supervised Learning: In Supervised learning, an AI system is presented with data which is labelled, which means that each data tagged with the correct label.The supervised learning is categorized into 2 other categories which are “Classification” and “Regression”. Unsupervised Learning:In unsupervised learning, an AI system is presented with unlabeled, un-categorized data and the system’s algorithms act on the data without prior training. The output is dependent upon the coded algorithms.

  7. Training and Testing the model on DATA For training a model we initially split the model into 3 three sections which are ‘Training data’ ,‘Validation data’ and ‘Testing data’. You train the classifier using ‘training data set’, tune the parameters using ‘validation set’ and then test the performance of your classifier on unseen ‘test data set’. An important point to note is that during Machine Learning training in Delhi is the classifier only the training and/or validation set is available. The test data set must not be used during training the classifier. The test set will only be available during testing the classifier. D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  8. Evaluation Model Evaluation is an integral part of the model development process. It helps to find the best model that represents our data and how well the chosen model will work in the future. To improve the model we might tune the hyper-parameters of the model and try to improve the accuracy and also looking at the confusion matrix to try to increase the number of true positives and true negatives. D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  9. Why should you choose Machine Learning? • Data is just too much for human processing and analysis. There is just too much data being produced and without an automated system based on machine learning to learn from such systems, we are nowhere. • And it's getting better. With new deep learning based systems, data engineering and preprocessing costs are dropping. D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

  10. We hope you’ll use these tips and For more go to :- http://pythonandmltrainingcourses.com/courses/best-machine-learning-course-in-delhi/ • THANK YOU D-58, Red FM Road, Sector 2, D Block, Sector 2, Noida, Uttar Pradesh 201301 092121 72602 http://pythonandmltrainingcourses.com

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