Project - Classify Clothes from Fashion MNIST Dataset using Machine Learning Techniques

Project - Classify Clothes from Fashion MNIST Dataset using Machine Learning Techniques

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12 Concepts | 7 Questions | 11 Assessments | 1,850 Learners

Welcome to this project on Classify Clothes from Fashion MNIST Dataset with a couple of Machine Learning algorithms like SGD Classifier, XGBClassifier, Softmax Regression (multi-class LogisticRegression), DecisionTreeClassifier, RandomForestClassifier, Ensemble (with soft voting) using scikit-learn. In this project, you will use Python and scikit-learn to build Machine Learning models, and apply them to predict the class of clothes from Fashion MNIST Dataset.

In this end-to-end Machine Learning project, you will get a hands-on overview of how to methodologically solve a machine learning classification problem. As a part of it, you will understand various methods of improvising the models using hyperparameter tuning, dimensionality reduction using the corresponding scikit-learn classes. You will also evaluate the performance of your final ensembling model using various performance metrics.

Skills you will develop:

  1. scikit-learn
  2. Machine Learning
  3. Hyperparameter Tuning
  4. Dimensionality Reduction
  5. Python Programming
  6. Ensemble modeling
  7. Data Preprocessing
  8. Pandas

Instructor:

Founder, CloudxLab.com