Fix missing images issue

notebooks/bytopic/dask/02_dask_arrays.ipynb

@@ -115,9 +115,10 @@
     "- we can specify the chunks argument. \"Chunks\" describes how the array is split up over many small pieces.\n",
     "- we can perform large computations by performing many smaller computations\n",
     "\n",
-    "![](../../../assets/dask-array-black-text.svg)\n",
     "\n",
-    "source: [Dask Array Documentation](http://dask.pydata.org/en/latest/array-overview.html)"
+    "![dask-array-black-text](../../../assets/dask-array-black-text.svg)\n",
+    "\n",
+    "source: [Dask Array Documentation](https://docs.dask.org/en/latest/array.html)"
    ]
   },
   {
@@ -172,7 +173,9 @@
     "### Task Graph\n",
     "\n",
     "\n",
-    "When working with dask, dask builds up a graph of blocked tasks to execute. This task graph is also known as Directed Acyclic Graph (DAG). A DAG is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies.\n",
+    "![dask-dag](../../../assets/dask-dag.gif)\n",
+    "\n",
+    "When working with dask, dask builds up a graph of blocked tasks to execute. This task graph is also known as **Directed Acyclic Graph (DAG)**. A DAG is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies.\n",
     "\n",
     "Dask allows us to visualize the task graph that gets executed when the computation is triggered. To see what this graph looks like, we call `.visualize()` on a dask object:"
    ]
@@ -288,7 +291,7 @@
    "source": [
     "<div class=\"alert alert-block alert-warning\">\n",
     "\n",
-    "Do not try to visualize `big_ones.visualize()` this array!! We repeat, do not visualize the graph for this array because it is too big, and it may cause your notebook server to crash! \n",
+    "Do not try to visualize big_ones.visualize() this array!! We repeat, do not visualize the graph for this array because it is too big, and it may cause your notebook server to crash! \n",
     "\n",
     "</div>"
    ]
@@ -426,5 +429,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

notebooks/bytopic/dask/04_dask_and_xarray.ipynb

@@ -233,7 +233,7 @@
    "source": [
     "<div class=\"alert alert-block alert-info\">\n",
     "\n",
-    "For this case, using the matplotlib approach is okay. However, if your data is too high-resolution, visualizing with matplotlib can be slow and less efficient.\n",
+    "For this case, using the matplotlib approach is okay. However, if your data is too high-resolution, visualizing with matplotlib can be slow and less efficient. Instead, you may want to visualize slices/subsets of the data on the fly. This is where interactive visualization comes in handy.\n",
     "\n",
     "</div>"
    ]
@@ -406,5 +406,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }