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Update Installation Guide #40

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Expand Up @@ -24,6 +24,39 @@ version supports classification problems only. Let's start by looking at some
classic classification problems and see how the framework can automatically find competitive
model architectures.

## Installation using Anaconda
In this section, we explain how to install necessary enviroment through Anaconda
1. Install AnaConda, please refer to https://docs.anaconda.com/anaconda/install/
2. Create new environment with Python3.8
```console
conda create -n auto_search python=3.8
```
3. Activate the new environment
```console
conda activate auto_search
```
4. Clone the repo
```console
git clone https://github.com/google/model_search.git
cd model_search/
```
5. Install Requirements
```console
pip install -r requirements.txt
```
6. Install Protobuf
```console
conda install -c anaconda protobuf
```
7. Compile Protobuf
```console
protoc --python_out=./ model_search/proto/phoenix_spec.proto
protoc --python_out=./ model_search/proto/hparam.proto
protoc --python_out=./ model_search/proto/distillation_spec.proto
protoc --python_out=./ model_search/proto/ensembling_spec.proto
protoc --python_out=./ model_search/proto/transfer_learning_spec.proto
```

## Getting Started
Let us start with the simplest case. You have a csv file where the features are numbers
and you would like to run let AutoML find the best model architecture for you.
Expand Down