docs: add a Getting Started Section

nx/guides/getting_started/installation.md

@@ -0,0 +1,186 @@
+# Installation
+
+The only prerequisite for installing Nx is Elixir itself. If you don´t have Elixir installed
+in your machine you can visit this [intallation page](https://elixir-lang.org/install.html).
+
+There are several ways to install Nx (Numerical Elixir), depending on your project type and needs.
+
+## Using Mix in a standardElixir Project
+
+If you are working inside a Mix project, the recommended way to install Nx is by adding it to your mix.exs dependencies:
+
+1. Open mix.exs and modify the deps function:
+
+```elixir
+defp deps do
+  [
+    {:nx, "~> 0.5"}  # Install the latest stable version
+  ]
+end
+```
+
+2. Fetch the dependencies, run on the terminal:
+
+```sh
+mix deps.get
+```
+
+## Installing Nx from GitHub (Latest Development Version)
+
+If you need the latest, unreleased features, install Nx directly from the GitHub repository.
+
+1. Modify mix.exs:
+
+```elixir
+defp deps do
+  [
+    {:nx, github: "elixir-nx/nx", branch: "main"}
+  ]
+end
+
+```
+
+2. Fetch dependencies:
+
+```sh
+mix deps.get
+
+```
+
+## Installing Nx in a Standalone Script (Without a Mix Project)
+
+If you don’t have a Mix project and just want to run a standalone script, use Mix.install/1 to dynamically fetch and install Nx.
+
+```elixir
+Mix.install([:nx])
+
+require Nx
+
+tensor = Nx.tensor([1, 2, 3])
+IO.inspect(tensor)
+
+```
+
+Run the script with:
+
+```sh
+elixir my_script.exs
+
+```
+
+Best for: Quick experiments, small scripts, or one-off computations.
+
+## Installing the Latest Nx from GitHub in a Standalone Script
+
+To use the latest development version in a script (without a Mix project):
+
+```elixir
+Mix.install([
+  {:nx, github: "elixir-nx/nx", branch: "main"}
+])
+
+require Nx
+
+tensor = Nx.tensor([1, 2, 3])
+IO.inspect(tensor)
+```
+
+Run:
+
+```sh
+elixir my_script.exs
+
+```
+
+Best for: Trying new features from Nx without creating a full project.
+
+## Installing Nx with EXLA for GPU Acceleration
+
+To enable GPU/TPU acceleration with Google’s XLA backend, install Nx along with EXLA:
+
+1. Modify mix.exs:
+
+```elixir
+defp deps do
+  [
+    {:nx, "~> 0.5"},
+    {:exla, "~> 0.5"}  # EXLA (Google XLA Backend)
+  ]
+end
+```
+
+2. Fetch dependencies:
+
+```sh
+mix deps.get
+```
+
+3. Run with EXLA enabled:
+
+```elixir
+EXLA.set_preferred_backend(:tpu)
+```
+
+Best for: Running Nx on GPUs or TPUs using Google’s XLA compiler.
+
+## Installing Nx with Torchx for PyTorch Acceleration
+
+To run Nx operations on PyTorch’s backend (LibTorch):
+
+1. Modify mix.exs:
+
+```elixir
+defp deps do
+  [
+    {:nx, "~> 0.5"},
+    {:torchx, "~> 0.5"}  # PyTorch Backend
+  ]
+end
+
+```
+
+2. Fetch dependencies:
+
+```sh
+mix deps.get
+```
+
+3. Run with EXLA enabled:
+
+```elixir
+Torchx.set_preferred_backend()
+```
+
+Best for: Deep learning applications with PyTorch acceleration.
+
+## Installing Nx with OpenBLAS for CPU Optimization
+
+To optimize CPU performance with OpenBLAS:
+
+1. Install OpenBLAS (libopenblas):
+   - Ubuntu/Debian:
+     ```sh
+     sudo apt install libopenblas-dev
+     ```
+   - MacOS (using Homebrew):
+     ```sh
+     brew install openblas
+     ```
+2. Modify mix.exs:
+
+```elixir
+defp deps do
+  [
+    {:nx, "~> 0.5"},
+    {:openblas, "~> 0.5"}  # CPU-optimized BLAS backend
+  ]
+end
+```
+
+3. Fetch dependencies:
+
+```sh
+mix deps.get
+```
+
+Best for: Optimizing CPU-based tensor computations.

nx/guides/getting_started/quickstart.livemd

@@ -106,6 +106,8 @@ Names make your code more expressive:
 Nx.tensor([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]], names: [:batch, :height, :width])
 ```
 
+We created a tensor of the shape `{3, 3}`, and two axes named `height` and `width`.
+
 You can also leave dimension names as `nil` (which is the default):
 
 ```elixir
@@ -128,7 +130,7 @@ tensor = Nx.tensor([[1, 2], [3, 4]], names: [:y, :x])
 tensor[[0, 1]]
 ```
 
-Negative indices will start counting from the end of the axis. 
+Negative indices will start counting from the end of the axis.
 `-1` is the last entry, `-2` the second to last and so on.
 
 ```elixir
@@ -167,6 +169,23 @@ Now,
 # ...your code here...
 ```
 
+### Tensor shape and reshape
+
+```elixir
+Nx.shape(tensor)
+```
+
+We can also create a new tensor with a new shape using `Nx.reshape/2`:
+
+```elixir
+Nx.reshape(tensor, {1, 4}, names: [:batches, :values])
+```
+
+This operation reuses all of the tensor data and simply
+changes the metadata, so it has no notable cost.
+
+The new tensor has the same type, but a new shape.
+
 ### Floats and Complex numbers
 
 Besides single-precision (32 bits), floats can have other kinds of precision, such as half-precision (16) or
@@ -177,13 +196,13 @@ Nx.tensor([0.0, 0.2, 0.4, 1.0], type: :f16)
 ```
 
 ```elixir
-Nx.tensor([0.0, 0.2, 0.4, 1.0, type: :f64)
+Nx.tensor([0.0, 0.2, 0.4, 1.0], type: :f64)
 ```
 
 Brain floats are also supported:
 
 ```elixir
-Nx.tensor([0.0, 0.2, 0.4, 1.0, type: :bf16)
+Nx.tensor([0.0, 0.2, 0.4, 1.0], type: :bf16)
 ```
 
 Certain backends and compilers support 8-bit floats. The precision

nx/mix.exs

@@ -59,6 +59,7 @@ defmodule Nx.MixProject do
         "CHANGELOG.md",
         "guides/intro-to-nx.livemd",
         "guides/getting_started/introduction.md",
+        "guides/getting_started/installation.md",
         "guides/getting_started/quickstart.livemd",
         "guides/advanced/vectorization.livemd",
         "guides/advanced/aggregation.livemd",
@@ -114,7 +115,7 @@ defmodule Nx.MixProject do
         ]
       ],
       groups_for_extras: [
-        Getting_Started: ~r"^guides/getting_started/",
+        "Getting Started": ~r"^guides/getting_started/",
         Exercises: ~r"^guides/exercises/",
         Advanced: ~r"^guides/advanced/"
       ]