Machine Learning with Python & Data Science from Scratch

It is not necessary to work on the projects associated with your job profile; you can work overtime by working on some projects which are not related to your job profile but goes perfectly with your skill sets. It would let to have a good impression over your boss, which would further lead to promotions. It might lead to a change in your role in the organization. This would lead you to the roadmap of your career in this field. Python is a high-level scripting language. It is easy to learn and robust than other words because of its dynamic nature and simple syntax which allows small lines of code. Included indentation and object-oriented, functional programming make it simple. Such advantages of Python makes it different from another language, and that's why Python is preferred for development in companies mostly. In industries, machine learning using python has become popular. This is because it has standard libraries that are used for scientific and numerical calculations. Also, it can be operated on Linux, Windows, Mac OS, and UNIX.

Data science is the application of a combination of mathematical, statistical, analytical and programming skills for the collection, organization, and interpretation of data to allow effective and proper management of the business whose data it is.

The job of such a scientist is trending all over the world. The demand for such scientists is huge, more than the number of available candidates. A recent report explained that the need for these scientists has increased by more than 50% since last year. These scientists often referred to as big data wranglers, are a perfect blend of mathematician and computer scientist.

Data science is a field of study that is growing at a fast pace. From big tech companies to E-commerce companies to websites and many others are now relying on data science. Amount of data that is collected by these companies are without any bounds. Semi-structure to big unstructured data is stored in large frameworks of these companies. Now the question is how to use this.

What you will gain in this book:

- What is meant by machine learning?

- A short history of machine learning

- Machine learning - automation within a knowledge

- The challenges of machine learning

- Advantages and disadvantages of machine learning language

- Machine learning in robotics

- Machine learning applications

- Machine learning algorithms

- How machine learning is changing the world -- and your everyday life

Why Is Data Science Widely Used? Why Should You Study Data Science? Why Should One Consider Data Science As A Career? Data Science: An Exciting Career Option Types of Data Loss and Recovery Options Data Science and Its Wide Range of Applications What Are the Programming Languages Required for Data Science? Meaning of Data Science in Depth 4 Weird Ways How Data Is Used Around the World 5 Reasons Why Data Science Could Be the Advertising Wave of the Future