One of the main reasons why Python is widely used in the scientific and research communities is because of its ease of use and simple syntax which makes it easy to adapt for people who do not have an engineering background. It is also more suited for quick prototyping.
According to engineers coming from academia and industry, deep learning frameworks available with Python APIs, in addition to the scientific packages have made Python incredibly productive and versatile. There has been a lot of evolution in deep learning Python frameworks and it’s rapidly upgrading. It provides great libraries to deals with data science application. It cover following Modules.
• Data exploration & analysis.
• Data visualization.
• Classical machine learning.
• Deep learning.
• Data storage and big data frameworks
• Odds and ends.
We cover all the topics in deep theoretical and practical with projects.