* **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.

### Concurrency + Parallelism: Web + Machine Learning

          if (!foundAndRemovedExactReference(forgetMeNot, moved.replaced)) {
            skipMe.add(moved.replaced);
          }
        }
        cursor--;
        nextCursor--;
      } else { // we must have set lastFromForgetMeNot in next()
        checkState(removeExact(requireNonNull(lastFromForgetMeNot)));
        lastFromForgetMeNot = null;
      }
    }

    // ===================================================================================
    //                                                                     Aggregation Set
    //                                                                           =========

    public void filter(String name, EsAbstractConditionQuery.OperatorCall<BsDuplicateHostCQ> queryLambda,

    // ===================================================================================
    //                                                                     Aggregation Set
    //                                                                           =========

    public void filter(String name, EsAbstractConditionQuery.OperatorCall<BsRoleTypeCQ> queryLambda,

    // ===================================================================================
    //                                                                     Aggregation Set
    //                                                                           =========

    public void filter(String name, EsAbstractConditionQuery.OperatorCall<BsRelatedQueryCQ> queryLambda,

            }
            return;
        }

        if (logger.isInfoEnabled()) {
            logger.info("Checking URL: {}", robotTxtUrl);
        }
        // add url to a set
        crawlerContext.getRobotsTxtUrlSet().add(robotTxtUrl);

        final HttpGet httpGet = new HttpGet(robotTxtUrl);

        // request header
        for (final Header header : requestHeaderList) {

window.innerWidth\n    this._scrollbarWidth = this._getScrollbarWidth()\n  }\n\n  _setScrollbar() {\n    if (this._isBodyOverflowing) {\n      // Note: DOMNode.style.paddingRight returns the actual value or '' if not set\n      //   while $(DOMNode).css('padding-right') returns the calculated value or 0 if not set\n      const fixedContent = [].slice.call(document.querySelectorAll(SELECTOR_FIXED_CONTENT))\n      const stickyContent = [].slice.call(document.querySelectorAll(SELECTOR_STICKY_CONTENT))\n\n      // Adjust...

            }
        }
    }

    // ===================================================================================
    //                                                                           Query Set
    //                                                                           =========
    public void setId_Equal(String id) {
        setId_Term(id, null);
    }

  }

  /**
   * Exception thrown by a {@link Ordering#explicit(List)} or {@link Ordering#explicit(Object,
   * Object[])} comparator when comparing a value outside the set of values it can compare.
   * Extending {@link ClassCastException} may seem odd, but it is required.
   */
  static class IncomparableValueException extends ClassCastException {
    final Object value;

pkg image, method (*CMYK) CMYKAt(int, int) color.CMYK
pkg image, method (*CMYK) ColorModel() color.Model
pkg image, method (*CMYK) Opaque() bool
pkg image, method (*CMYK) PixOffset(int, int) int
pkg image, method (*CMYK) Set(int, int, color.Color)
pkg image, method (*CMYK) SetCMYK(int, int, color.CMYK)
pkg image, method (*CMYK) SubImage(Rectangle) Image
pkg image, method (Rectangle) At(int, int) color.Color