gg

Author: Programmer-RD-AI

.ipynb_checkpoints/06-checkpoint.ipynb

@@ -1,9 +1,31 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d2b493b7-ef5e-4612-b094-52d84aac0ff3",
+   "metadata": {},
+   "source": [
+    "## What is a machine learning research paper?\n",
+    "\n",
+    "A machine learning research paper is a scientific paper that details findings of a research group on a specific area.\n",
+    "\n",
+    "The contents of a machine learning research paper can vary from paper to paper but they generally follow the structure:\n",
+    "\n",
+    "| **Section** | **Contents** |\n",
+    "| ----- | ----- | \n",
+    "| **Abstract** | An overview/summary of the paper's main findings/contributions. |\n",
+    "| **Introduction** | What's the paper's main problem and details of previous methods used to try and solve it. |\n",
+    "| **Method** | How did the researchers go about conducting their research? For example, what model(s), data sources, training setups were used? |\n",
+    "| **Results** | What are the outcomes of the paper? If a new type of model or training setup was used, how did the results of findings compare to previous works? (this is where **experiment tracking** comes in handy) |\n",
+    "| **Conclusion** | What are the limitations of the suggested methods? What are some next steps for the research community? |\n",
+    "| **References** | What resources/other papers did the researchers look at to build their own body of work? |\n",
+    "| **Appendix** | Are there any extra resources/findings to look at that weren't included in any of the above sections? |"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "36b201f6-5ca0-4a27-80ba-52002d17fd8d",
+   "id": "d8bc9bda-c7e2-407d-99d5-ad387f49b625",
    "metadata": {},
    "outputs": [],
    "source": []

.ipynb_checkpoints/07-checkpoint.ipynb

@@ -1,56 +1,31 @@
 {
  "cells": [
   {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "36b201f6-5ca0-4a27-80ba-52002d17fd8d",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import torch.nn.functional as F"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "51230b85-9fb5-439b-b70a-2908b598341f",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import torchtext.functional as F\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "46206105-8864-4466-b1eb-1df21696cccf",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "tensor([1, 2, 3])"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "cell_type": "markdown",
+   "id": "d2b493b7-ef5e-4612-b094-52d84aac0ff3",
+   "metadata": {},
    "source": [
-    "F.to_tensor([1,2,3],padding_value=5)"
+    "## What is a machine learning research paper?\n",
+    "\n",
+    "A machine learning research paper is a scientific paper that details findings of a research group on a specific area.\n",
+    "\n",
+    "The contents of a machine learning research paper can vary from paper to paper but they generally follow the structure:\n",
+    "\n",
+    "| **Section** | **Contents** |\n",
+    "| ----- | ----- | \n",
+    "| **Abstract** | An overview/summary of the paper's main findings/contributions. |\n",
+    "| **Introduction** | What's the paper's main problem and details of previous methods used to try and solve it. |\n",
+    "| **Method** | How did the researchers go about conducting their research? For example, what model(s), data sources, training setups were used? |\n",
+    "| **Results** | What are the outcomes of the paper? If a new type of model or training setup was used, how did the results of findings compare to previous works? (this is where **experiment tracking** comes in handy) |\n",
+    "| **Conclusion** | What are the limitations of the suggested methods? What are some next steps for the research community? |\n",
+    "| **References** | What resources/other papers did the researchers look at to build their own body of work? |\n",
+    "| **Appendix** | Are there any extra resources/findings to look at that weren't included in any of the above sections? |"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6dbd7aae-0a59-457e-b33e-465d1eb153c1",
+   "id": "d8bc9bda-c7e2-407d-99d5-ad387f49b625",
    "metadata": {},
    "outputs": [],
    "source": []