Andrew Park - Data Science for Beginners: 4 Books in 1: Python Programming, Data Analysis, Machine Learning. A Complete Overview to Master The Art of Data Science From Scratch Using Python for Business
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Would you like to learn how to program in Python? You have no prior knowledge about Python? Or, you just want to refresh your memory? You are a little bit afraid because everything about Python looks complicated and scary?
Well, the solution is right in front of you. With this bundle in your hands, youll go from beginner to pro in no time. These books and guides are specifically designed for people that have little or no prior knowledge about Python Programming.
Everything inside is designed to be step-by-step, so you can have an easier time understanding the concepts around it.
This comprehensive bundle contains everything youll need to know to successfully implement Data Science techniques and Machine Learning algorithms through Python. From basic tutorials and exercises to expert coding techniques.
Heres a sneak peek of what youll discover inside this bundle:
- Python for beginners: Learn quickly and easily the basics of programming with Python. You will find a comprehensive guide on how to get everything up and running!
- Everything about data types, variables, and structures: Discover the basics of data types, variables, and structures. Learn what they represent, and why are they so important
- Essential programming tools: Discover what are the best and essential tools that youll need to use while programming with Python. Of course, learn how to use them.
- Everything about Data Analysis: Discover why is it so important for Python programmers. Find out its methods and applications. When properly using Data Analysis, everything is guaranteed to run smoother.
- Basics of Data Science: Find out the importance of Data Science, and its correlation with programming and Machine Learning. Learn the concepts behind Data Mining, Deep Learning, and Big Data.
- A the comprehensive guide about Neural Networks: What they are, how they work, and most importantly how to create one. Learn the best way to use data for prediction and Deep Learning.
- Combining Python, Machine Learning, and Data Science: Comprehensive guide to combining Python, Machine Learning, and Data Science. Quick and easy ways to learn how to make amazing and useful programs.
It doesnt matter if you are a beginner, or you never have coded before. This guide will slowly ease you into the world of Data Science. While most of the other similar books put the focus on theory and complicated concepts, this one is designed specifically for beginners.
Furthermore, topics are carefully selected to give you broad exposure, while not overwhelming you with too much information. Also, unlike the majority of books, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples.
Data Science for Beginners is here to provide you with simplified step-by-step learning, so youll have an easier time understanding and acquiring knowledge.
All you have to do is to click on that BUY NOW button, and you will be able to begin your journey to mastering Python, Machine Learning and Data Science!Andrew Park: author's other books
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Data Science for Beginners
4 Books in 1:
Python Programming, Data Analysis,
Machine Learning.
A Complete Overview for Beginners to Master The Art of Data Science From Scratch Using Python.
Andrew Park
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Python for Beginners
The Ultimate Crash Course to Learn Python in 7 days with Step-by-Step Guidance and Hands-On Exercises
Table of Contents
Python is among the top programming languages that universities and industries are preferring to teach and use respectively. The charm of Python is hidden in the fact that it has extremely large applications in a wide range of fields. Most people abhor Python because of its use in building artificial intelligence models. They fear that these Python-powered AI models will drive people out of different industries and snatch their jobs. They quote the example of Teslas driverless taxi program by which Tesla tends to replace Ubers taxis in the US market. But the reality is different. In fact, Python-powered AI models will create many more jobs than they are going to remove. For example, building these models will become an independent industry. Also, the implementation of these AI models will become a new job sector.
Data science is going to take the corporate world by storm. Data science is based on Python programming, as more and more companies are now moving in a neck-on-neck competition. All they crave is for a way to take an edge over their competitors. They do each thing for power and to get ahead. In this regard, Python seems to be promising. Python-backed data science tends to equip industries with sophisticated data about past and present sales patterns, which can help corporate sector CEOs make wiser decisions about sales and development of marketing strategies.
The biggest advantage for learners of Python is that you dont have to compile the code. In C++, you have to compile the entire program first and then run it. Only then you will be able to see whether your program runs or returns an error. Python offers the same level of programming and even at a higher stage, but still, it is an interpreted language that can be easily written, edited, and corrected.
Python is very easy to read and learn. You can easily read source codes for different programs that are created by other programmers. But no matter how easy it is on the outside to read and learn, it needs, like all the other programming languages, dedicated practice. You will have to get to the Python editor and practice all codes. In the beginning, you can take the code and just paste it in the editor to see the results. In the second phase, you can make minor edits to the code and see the results. In the third phase, you will be able to completely reshape a program and see how it runs in the Python shell. Given the increasing applications of Python, learning it is extremely profitable from the angle of the global job market. Python can give you the much-needed edge over others when it comes to securing high paid jobs.
The up-to-date edition with the binaries, current source codes, documentation, latest news, etc. can be accessed at the official Python website: http://www.Python.org/
Here, you can download the documentation for Python from the site. It is accessible in various formats like PDF, HTML, and PostScript.
Python Documentation Website: www.Python.org/doc/
Python Environment Variables:
Variable | Description |
PYTHONPATH | It is similar to PATH. This variable foretells the Python interpreter as to where it can locate the module files that you can import in a program. PYTHONPATH must have a Python source library directory and the directories in which your Python code is present. PYTHONPATH is sometimes set by the Python installer automatically. |
PYTHONSTARTUP | It has the path for the initialization file which contains Python source codes that are executed every time you work on the interpreter. This file is often named .Pythonrc.py in Unix, which usually has commands that can load the utilities or can modify the PYTHONPATH. |
PYTHONCASEOK | This is used in Windows OS for instructing Python to find case-insensitive matches in an import statement. You can set this to any random value for activating it. |
PYTHONHOME | It is an alternative search path that is embedded in PYTHONSTARTUP or PYTHONPATH directories for switching the module libraries very easy. |
Python can be run on a system in three ways.
You can start by entering Python and then begin programming in its interpreter by beginning from the command line on any platform that provides a command line interpreter or a shell window.
A list of command line options is given in the table below.
Option | Description |
-d | Provide the output after debugging |
-O | Optimized byte code generation i.e. the .pyo file is generated |
-S | Dont run the import site for searching Python paths in a startup. |
-v | Details of the import statement |
-X | Disable the class-based built-in exceptions |
-c cmd | It runs Python script sent in cmd String |
File | The python script is run from the given file |
Calling an interpreter on your application can help you run and execute your Python script in the command line.
It is possible to run Python from a GUI too. The one thing you require is a system that supports Python.
Python supports different data types. Each variable should belong to one of the data types supported in Python. The data type determines the value that can be assigned to a variable, the type of operation that may be applied to the variable as well as the amount of space assigned to the variable. Let us discuss different data types supported in Python.
These data types help in the storage of numeric values. The creation of number-objects in Python is done after we have assigned a value to them. Consider the example given below:
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