*** Proof of Product ***
Exploring the Essential Features of “Stone River eLearning – Machine Learning for Apps”
Content Proof:
- 1 What is Machine Learning C
- 0. Proof.pdf
- 1 What is Machine Learning.ts
- 2 Basics of Machine Learning.ts
- 3 Installing Anaconda.ts
- 4 Downloading-Setting Up Atom.ts
- 5 Variables in Python.ts
- 6 Arrays & Tuples in Python.mp4
- 7 Functions, Conditionals.ts
- 8 Importing Modules in
- 9 What is scikit-learn- Why.ts
- 10 Installing scikit-learn.ts
- 11 Intro to the Iris Dataset.ts
- 12 Datasets-Features.ts
- 13 Loading the Iris Dataset.ts
- 14 Creating – Training.ts
- 15 Testing Prediction Accuracy.mp4
- 16 Building our Own KNeighbors.ts
- 17 What is Keras- Why use it.ts
- 18 What is a Convolutional.ts
- 19 Installing Keras with Anaconda.ts
- 20 Preparing Dataset for a
- 21 Building-Visualizing habc.ts
- 22 Building – Visualizing.ts
- 23 Training CNN – Evaluating.ts
- 24 Switching Python Environments.ts
- 25 Intro to App – Handwriting.ts
- 26 Building Interface – Wiring Up.ts
- 27 Drawing On Screen.ts
- 28 Importing Core ML Model.ts
- 29 Utilizing Core ML – Vision.ts
- 30 Handling – Displaying.ts
- 31 Intro to App – Core ML.ts
- 32 What is Machine Learning.ts
- 33 What is Core ML.ts
- 34 Creating Xcore Project.ts
- 35 Building ImageVC in Interface.ts
- 36 Creating ImageCell & Subclass.ts
- 37 Creating FoodItems Helper File.ts
- 38 Creating Custom 3×3.ts
- 39 Choosing, Downloading.ts
- 40 Passing Images Through.ts
- 41 Passing Images Through.ts
- 41 Challenge – Core ML.ts
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