Python for Data Visualization & Fraud Detection Bootcamp

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Created by Online Training Plus | Video: h264 1280x720 | Audio: AAC 48KHz 2ch | Duration: 30:21 H/M | Lec: 99 | 22.6 GB | Language: English | Sub: English [Auto-generated]

Learn to code in a #1 programming language with step by step examples! Learn matDescriptionlib, Tensorflow, statistics & more!

What you'll learn
Make a Credit Card Fraud Detection Model in Python. Learn how to keep your data safe!
Learn TensorFlow and how to build models of linear regression
Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.
Create basic line and scatter Descriptions with MatDescriptionlib 1.5.
Read finance data directly from Yahoo.
Customise our graphs with visuals, a title, labels, text and a legend.
Recognize types of visualization: histograms, pie charts, and box and whisker Descriptions.
Understand basic 3D Descriptionting.
Perform in-depth customization of Description structure.
And more!
Requirements
Download Anaconda 4.2, the free data science platform by Continuum, which contains Python 3.5 and MatDescriptionlib.
Otherwise, you can download and install Python 3.5 and MatDescriptionlib for free online.
For fraud detection model building, we will use PyCharm Community Edition
Topics involve intermediate math, so familiarity with university-level math is very helpful.
Description
Do you want to learn Python, MatDescriptionlib, and Tensorflow? You've come to the right place.
This course was funded by a wildly successful Kickstarter.
Do you want to learn how to visualize data? Enroll in this course to learn how to do so directly in code. This course is suitable for coding beginners because we begin with a complete introduction to coding. Then we delve deep into using MatDescriptionlib, a Python 2D Descriptionting library.
Learn to Use Python in Anaconda and PyCharm
Python is a popular coding language used for websites like YouTube and Instagram. You learn the basics of programming, including topics like variables, functions, and if statements. You learn about data structures such as lists, dictionaries, and sets. We cover how to use for and while loops, how to handle user input and output, file input and output.
Included in this course is material for beginners to get comfortable with the interfaces. Please note that we reuse this content in similar courses because it is introductory material. You can find some material in this course in the following related courses:
Predict fraud with data visualization & predictive modeling!
Detect Fraud and Predict the Stock Market with TensorFlow
Make 2D & 3D Graphs in Python with MatDescriptionlib for Beginners
Python Data Science and Machine Learning Bootcamp with Keras
Making Games in Unity and Graphs in Python using MatDescriptionlib
Build Games and Learn with Examples
We apply our knowledge to build a fully functional tic-tac-toe game. You learn classes, methods, attributes, instancing, and class inheritance. We make an additional Blackjack game! You learn how to solve errors that can occur when you work as a programmer.
Apply Your Python Knowledge to MatDescriptionlib
For data visualization, you will learn many cool features of MatDescriptionlib that we can use for data visualization. We show you how to make line Descriptions, scatter Descriptions, candlestick Descriptions.
You learn how to customize the visuals of your graph, add text, and annotate graphs. And much more!
And More
You will also learn to work with TensorFlow and PyCharm to analyze credit card fraud. And many more topics in this huge masterclass from the Mammoth Interactive team.
Who this course is for?
Absolute beginners who want to learn to code for the web in the popular Python programming language.
Beginners who want to learn how to use data science to make graphs.
Experienced programmers who want to learn a 2D Descriptionting library for Python.
Anyone who wants to learn data modeling and visualization.
[url=https://www.udemy.com/course/completepythonbootcamp/]https://www.udemy.com/course/completepythonbootcamp/
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Code:

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