* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.
* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

/**
 * Implementation detail for the internal structure of {@link Range} instances. Represents a unique
 * way of "cutting" a "number line" (actually of instances of type {@code C}, not necessarily
 * "numbers") into two sections; this can be done below a certain value, above a certain value,
 * below all values or above all values. With this object defined in this way, an interval can

// Submitted by Mario Siegenthaler <******@****.***>
linkyard-cloud.ch
linkyard.cloud

// Linode : https://linode.com
// Submitted by <******@****.***>
members.linode.com
*.nodebalancer.linode.com
*.linodeobjects.com
ip.linodeusercontent.com

// LiquidNet Ltd : http://www.liquidnetlimited.com/
// Submitted by Victor Velchev <******@****.***>

 * JMORRIS         <03>  UNIQUE      Registered
 *
 * MAC Address = 00-B0-34-21-FA-3B
 * </pre>
 *
 * </blockquote>
 *
 *  * The hostname of this machine is <code>JMORRIS2</code>. It is
 * a member of the group(a.k.a workgroup and domain) <code>BILLING-NY</code>. To
 * obtain an {@link java.net.InetAddress} for a host one might do:
 *
 * <pre>
 *
 * InetAddress addr = NbtAddress.getByName("jmorris2").getInetAddress();

    
    // Witness RPC interface
    private static final String WITNESS_INTERFACE_UUID = "ccd8c074-d0e5-4a40-92b4-d074faa6ba28";
    private static final int WITNESS_INTERFACE_VERSION = 1;
    
    // RPC operation numbers
    private static final int WITNESS_REGISTER = 0;
    private static final int WITNESS_UNREGISTER = 1;
    private static final int WITNESS_ASYNC_NOTIFY = 2;
    private static final int WITNESS_HEARTBEAT = 3;
    

* Validation for most (or all?) Python **data types**, including:
    * JSON objects (`dict`).
    * JSON array (`list`) defining item types.
    * String (`str`) fields, defining min and max lengths.
    * Numbers (`int`, `float`) with min and max values, etc.

* Validation for more exotic types, like:
    * URL.
    * Email.
    * UUID.
    * ...and others.

   */
  public void testEviction_maxWeight_zero() {
    CountingRemovalListener<Integer, Integer> removalListener = countingRemovalListener();
    IdentityLoader<Integer> loader = identityLoader();

    // Even numbers are free, odd are too expensive
    Weigher<Integer, Integer> evensOnly =
        new Weigher<Integer, Integer>() {
          @Override
          public int weigh(Integer k, Integer v) {
            return k % 2;

 *
 * @version $Revision$ $Date$
 */
@SuppressWarnings("all")
public final class InputLocation implements java.io.Serializable, Cloneable, InputLocationTracker {

    // --------------------------/
    // - Class/Member Variables -/
    // --------------------------/

    /**
     * The one-based line number. The value will be non-positive if
     * unknown.
     */
    private int lineNumber = -1;

    /**

- **MinIO creates erasure-coding sets of _2_ to _16_ drives per set.  The number of drives you provide in total must be a multiple of one of those numbers.**
- **MinIO chooses the largest EC set size which divides into the total number of drives or total number of nodes given - making sure to keep the uniform distribution i.e each node participates equal number of drives per set**.

    * objetos JSON (`dict`).
    * arrays JSON (`list`), definindo tipos dos itens.
    * campos String (`str`), definindo tamanho mínimo e máximo.
    * Numbers (`int`, `float`) com valores mínimos e máximos, etc.

* Validação de tipos mais exóticos, como:
    * URL.
    * Email.
    * UUID.
    * ...e outros.