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MATLAB is a high-level language
MATLAB Supports Object oriented programming. It also supports different types of programming constructs like Control flow statements (IF-ELSE, FOR, WHILE). MATLAB also supports structures like in C programming, Functional programming (writing functions to contain commonly used code and later calling them). It also contains Input / Output statements like disp() and input().
MATLAB has inbuilt graphics to enhance user experience. We can actually visualize whatever data is there in forms of plots and figures. It also supports processing of image and displaying them in 2D or 3D formats. We can visualize and manipulate our data across any of the three dimensions (1D, 2D, and 3D).
A Large Library of Mathematical Functions
MATLAB has a huge inbuilt library of functions required for mathematical analysis of any data. It has common math functions like sqrt. factorial etc. It has functions required for statistical analysis like median, mode and std (to find standard deviation), and much more.
MATLAB offers interactive environment by providing a GUI (Graphical user interface) and different types of tools like signal analyses and tuners. MATLAB also has tools for debugging and the development of any software.
Interact with Different Languages
We can write a set of codes (libraries) in languages like PERL and JAVA, and we can call those libraries from within the MATLAB itself. MATLAB also supports ActiveX and .NET libraries.
What Is MATLAB Programming?
MATLAB® is a programming platform designed specifically for engineers and scientists to analyze and design systems and products that transform our world. The heart of MATLAB is the MATLAB language, a matrix-based language allowing the most natural expression of computational mathematics.
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This is the process of altering data. We we select specific features hat can help to increase the models efficiency. There are some steps which are used to implement machien learning task;
Training, testing model and predicting the output.
Some words that are written by experienced machine learning experts; Much of the success of machine learning is actually success in engineering features that a learner can understand.
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Now a days data is increases day by day so that data scientist face the problem to run the large size data which need to implement using Spark. Data bricks is a data engineering tool that are used by companies to process and transform by large quantity of data.
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Many modern-day datasets are huge and truly exemplify “big data”. For example, the Facebook social graph is petabytes large (over 1M GB); every day, Twitter users generate over 12 terabytes of messages; and the NASA Terra and Aqua satellites each produce over 300 GB of MODIS satellite imagery per day. These raw data are far too large to even fit on the hard drive of an average computer, let alone to process and analyze. Luckily, there are a variety of modern technologies that allow us to process and analyze such large datasets in a reasonable amount of time.
A main goal of this assignment is to help students gain exposure to a variety of tools that will be useful in the future (e.g., future project, research, career). The reasoning behind intentionally including AWS, Azure and GCP (most courses use only one), because we want students to be able to try and compare these platforms as they evolve rapidly. This will help the students in the future. Should they need to select a cloud platform to use, they can make more informed decisions and be able to get started right away.
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Hire Data Bricks Expert
Databricks has excellent documentation and we defer to their guidance instead of reproducing it here. Follow these steps to get started:
1. Create a Community Edition (https://community.cloud.databricks.com/) account on Databricks. Do NOT select Databricks Platform - Free Trial; if you do, you will encounter many problems in the subsequent sections. More info: https://docs.databricks.com/getting-started/try-databricks.html
Hire AWS & PySpark Expert
You will try out PySpark for processing data on Amazon Web Services (AWS). Here you can learn more about PySpark and how it can be used for data analysis. You will be completing a task that may be accomplished using a commodity computer (e.g., consumer-grade laptops or desktops). However, we would like you to use this exercise as an opportunity to learn distributed computing on Amazon EC2, and to gain experience that will help you tackle more complex problems.
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Helpful tips/FAQs for special scenarios:
If GCP service is disabled for your google account, try the steps in this google support link
If you have any issues with GCP free credits, please fill out this form
Dimensionality Reduction Assignment help
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