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Easy books of Data Science for professionals: Get hired in Big Companies
- Get to know the five most important steps of data science
- Use your data intelligently and learn how to handle it with care
- Bridge the gap between mathematics and programming
- Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results
- Build and evaluate baseline machine learning models
- Explore the most effective metrics to determine the success of your machine learning models
- Create data visualizations that communicate actionable insights
- Learn the basics of linear algebra, statistics, and Probability how and when they're used in data science
- Collect, explore, clean, munge, and manipulate data
- Dive into the fundamentals of machine learning
- Implement models such as K-Nearest neighbors, nave Bayes, linear and logistic regression, decision trees, neural networks, and clustering
- Explore recommender systems, natural language processing, network analysis, produce, and databases
- If you are looking to start a new career that is in high demand, then you need to continue reading.
- Data scientists are changing the way big data is used in different institutions.
- Big data is everywhere, but without the right person to interpret it, it means nothing.
- So where do business find these people to help change their business?