Merge pull request #1395 from jaelgu/fix-hybrid

Fix typo

bootcamp/tutorials/quickstart/hybrid_search_with_milvus.ipynb

@@ -103,7 +103,7 @@
     "    obj = row.to_dict()\n",
     "    questions.add(obj[\"question1\"][:512])\n",
     "    questions.add(obj[\"question2\"][:512])\n",
-    "    if len(questions) > 500:  # Skip this if you want to use the full data\n",
+    "    if len(questions) > 500:  # Skip this if you want to use the full dataset\n",
     "        break\n",
     "\n",
     "docs = list(questions)\n",
@@ -153,7 +153,7 @@
     "\n",
     "We will set up the Milvus collection and create indices for the vector fields.\n",
     "\n",
-    "> - Setting the uri as a local file, e.g../milvus.db, is the most convenient method, as it automatically utilizes [Milvus Lite](https://milvus.io/docs/milvus_lite.md) to store all data in this file.\n",
+    "> - Setting the uri as a local file, e.g. \"./milvus.db\", is the most convenient method, as it automatically utilizes [Milvus Lite](https://milvus.io/docs/milvus_lite.md) to store all data in this file.\n",
     "> - If you have large scale of data, say more than a million vectors, you can set up a more performant Milvus server on [Docker or Kubernetes](https://milvus.io/docs/quickstart.md). In this setup, please use the server uri, e.g.http://localhost:19530, as your uri.\n",
     "> - If you want to use [Zilliz Cloud](https://zilliz.com/cloud), the fully managed cloud service for Milvus, adjust the uri and token, which correspond to the [Public Endpoint and API key](https://docs.zilliz.com/docs/on-zilliz-cloud-console#cluster-details) in Zilliz Cloud."
    ]
@@ -174,7 +174,7 @@
     ")\n",
     "\n",
     "# Connect to Milvus given URI\n",
-    "connections.connect(uri=\"milvus.db\")\n",
+    "connections.connect(uri=\"./milvus.db\")\n",
     "\n",
     "# Specify the data schema for the new Collection\n",
     "fields = [\n",