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An online diploma course in Machine Learning can make your career worth
- All the codes have been updated to work with Python 3.6 and 3.7
- The codes have been refactored to work with Google Colab
- Deep Learning and NLP
- Binary and multi-class classifications with deep learning
- Get the most up to date machine learning information possible, and get it in a single course!
- Set up a Python development environment correctly
- Gain complete machine learning toolsets to tackle most real-world problems
- Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, precision, recall, etc. and when to use them.
- Combine multiple models with by bagging, boosting or stacking
- Make use to unsupervised Machine Learning (ML) algorithms such as Hierarchical clustering, k-means clustering, etc. to understand your data
- Develop in Jupyter (IPython) notebook, Spyder and various IDE
- Communicate visually and effectively with Matplotlib and Seaborn
- Engineer new features to improve algorithm predictions
- Make use of train/test, K-fold, and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data
- Use SVM for handwriting recognition, and classification problems in general
- Use decision trees to predict staff attrition
- Apply the association rule to retail shopping datasets
- Anyone willing and interested to learn machine learning algorithm with Python
- Anyone who has a deep interest in the practical application of machine learning to real-world problems
- Anyone wishes to move beyond the basics and develop an understanding of the whole range of machine learning algorithms
- Any intermediate to advanced EXCEL users who are unable to work with large datasets
- Anyone interested to present their findings in a professional and convincing manner
- Anyone who wishes to start or transit into a career as a data scientist
- Anyone who wants to apply machine learning to their domain