Hands-On Neural Networks​: Build Machine Learning Models​

About this course

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 glo

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