Created by: Mammoth Interactive, John Bura
Credit Fraud Detection & Stock Analysis -- No Experience Required. Learn to Base Predictions With Python & Tensorflow
What you'll learn
Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.
Learn TensorFlow and how to build models of linear regression.
Make an image recognition model with CIFAR.
Make an app with Python that uses data to predict the stock market.
PyCharm Community Edition 2017.2
Build 2 complete projects start to finish -- with each step explained thoroughly by instructor Nimish Narang from Mammoth Interactive.
Hands-On Neural Networks: Build Machine Learning Models was funded by a #1 project on Kickstarter
Nimish is our cross-platform developer and has created over 20 other courses specializing in machine learning, Java, Android, SpriteKit, iOS and Core Image for Mammoth Interactive. When he's not developing, Nimish likes to play guitar, go to the gym and laze around at the beach.
Project #1 -- Learn to construct a model for credit card fraud detection. Our model will take in a list of transactions, some fraudulent and some legitimate. It will output the percentage at which it can calculate fraudulence and legitimacy, how accurate it is. We will also modify the model so that it output whether a specific transaction is fraudulent or legitimate if we pass them in one by one.
We will explore a dataset so that you fully understand it, and we will work on it. It's actually pretty hard to find a dataset of fraudulent/legitimate credit card transactions, but we at Mammoth Interactive have found everything for you and curated a step by step curriculum so that you can build alongside us.
We will manipulate the dataset so that it will be easy to feed into our model. We will build a computational graph with nodes and functions to run input through the mini neural network.
Machine Learning Projects Using Tensorflow -- Mammoth Interactive
Project #2 -- Learn to build a simple stock market prediction model that will predict whether the price stock will go up or down the next morning based on the amount of volume exchange for a given day
Any kind of global event can completely affect how stock prices fluctuate. As such we will build a simple model that only take in the volume exchange for a particular day and will only be used for day trading -- choosing whether to buy or sell at the end of the day. It is short term prediction.
We will NOT build a huge neural network that takes in thousands of data points and hours to train. We will build a simple model for you to expand upon. You will learn how to go through building a Tensorflow project and how you would get started with a stock prediction task.
You will get a solid base that you can expand upon. We will take previous stock data from the Investing site. Included are 8 CSV sheets for you to use to train and test your model for four different stocks.
Enroll now in Hands-On Neural Networks: Build Machine Learning Models with Mammoth Interactive
Who this course is for:
Topics involve intermediate math, so familiarity with university-level math is very helpful
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