Arrays are a powerful means of storing variables of the same data type (Integer, Float, String, etc.). To give you some context, if you have worked on Pandas DataFrames, which is a special case of 2 Dimensional Arrays, you would know what different operations you can perform and how you can handle datasets more effectively. Well with Arrays you can do most of that and much more and for that very reason they are used as the preferred Data Containers to run Machine Learning algorithms (in Modules such as Scipy and Scikit-learn). To simply put, "A good command on Arrays will take your understanding of Data Structures and their use to the next level", and this is exactly where this course comes in. Even if you've not worked on Arrays earlier, you can use this course to develop your understanding grounds-up.

Arrays are a powerful means of storing variables of the same data type (Integer, Float, String, etc.). To give you some context, if you have worked on Pandas DataFrames, which is a special case of 2 Dimensional Arrays, you would know what different operations you can perform and how you can handle datasets more effectively. Well with Arrays you can do most of that and much more and for that very reason they are used as the preferred Data Containers to run Machine Learning algorithms (in Modules such as Scipy and Scikit-learn). To simply put, "A good command on Arrays will take your understanding of Data Structures and their use to the next level", and this is exactly where this course comes in. Even if you've not worked on Arrays earlier, you can use this course to develop your understanding grounds-up.

Python is an object oriented programming language. It has become one of the significant languages of the world because whether be its machine learning or AI or its web development, each and every feature of python makes it important. It is used by many large companies like Google or YouTube for their many projects. This is why the need to learn the python programming language has emerged. If you are a beginner and struggling with what is python, why should you learn python and other significant details about it then don't panic this article is made about python programming for the absolute beginner.

Over the past several years the popularity of Python has grown rapidly. A big part of that has been the rise of Data Science, Machine Learning, and AI, all of which have high-level Python libraries to work with! When using Python for those types of work, it's often necessary to work with very large datasets. Those large datasets get read directly into memory, and are stored and processed as Python arrays, lists, or dictionaries. Working with such huge arrays can be time consuming; really that's just the nature of the problem.

Amazon SageMaker makes it easy to train and deploy Machine Learning models hosted on HTTP endpoints. However, in most cases you won't expose these endpoints directly. Pre-processing and post-processing steps are likely to be required: authentication, throttling, data transformation and enrichment, logging, etc. In this post, we will use AWS Chalice to build a web service acting as a front-end for a SageMaker endpoint. I've already written a couple of posts (here and here) on training and deploying SageMaker models, so I won't go into these details again.