You need to learn multiple concepts and technologies to get started in data science and machine learning. They include:
- Python for data science since it's the main language used in the field.
- How to manage data science and machine learning packages.
- How to build beautiful visualizations.
- How to use Scikit-learn to solve various machine learning problems.
- Various machine learning algorithms such as linear regression and logistic regression.
- How to deal with imbalanced data.
- Building deep learning models with deep learning libraries such as TensorFlow.
- Using top machine learning libraries such as XGBoost and LightGBM.
We have curated various data science and machine learning resources as PDFs, which are available for download below.
The PDFs available for download include:
- Data visualization guide
- Python for data science
- PIP and virtualenv
- Linear regression
- Decision trees
- Random forests
- K Nearest Neighbours
- Support vector machines
- Dask for big data
- How to handle imbalanced data
- Deep learning
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