remove pip install to avoid package conflict

Author: atqy

sagemaker-experiments/tensorflow2-california-housing-regression-experiment/tensorflow2-california-housing-regression-experiment.ipynb

@@ -2,7 +2,6 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "b673db31",
    "metadata": {},
    "source": [
     "## California Housing Regression Experiment\n",
@@ -24,7 +23,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6aa9af97",
    "metadata": {},
    "source": [
     "### Install Python Packages"
@@ -33,18 +31,25 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "07ef2630",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip list | grep sagemaker-experiments"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import sys\n",
     "\n",
-    "!{sys.executable} -m pip install sagemaker-experiments==0.1.31 matplotlib"
+    "!{sys.executable} -m pip install matplotlib"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5f6e0e4a",
    "metadata": {},
    "source": [
     "### Setup"
@@ -53,7 +58,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a919b135",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74,7 +78,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e64e12da",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -88,7 +91,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9fb68336",
    "metadata": {},
    "source": [
     "### Download California Housing dataset and upload to Amazon S3"
@@ -97,7 +99,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6ece115e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -132,7 +133,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b066d544",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -148,7 +148,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a2d2a6e",
    "metadata": {},
    "source": [
     "### Step 1 - Set up the Experiment\n",
@@ -158,7 +157,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c2f86710",
    "metadata": {},
    "source": [
     "### Create an Experiment"
@@ -167,7 +165,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4c1fbca9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -180,7 +177,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "581b6c8d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -194,7 +190,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9f872fca",
    "metadata": {},
    "source": [
     "### Step 2 - Track Experiment\n",
@@ -205,7 +200,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d0336132",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -218,7 +212,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7680ca71",
    "metadata": {},
    "source": [
     "If you want to run the following training jobs asynchronously, you may need to increase your resource limit. Otherwise, you can run them sequentially.\n",
@@ -229,7 +222,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "df3f4b99",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -296,7 +288,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "79d10cf4",
    "metadata": {},
    "source": [
     "### Compare the model training runs for an experiment\n",
@@ -307,7 +298,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "54457af4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -324,7 +314,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ad3c1940",
    "metadata": {},
    "source": [
     "Let's show the accuracy, epochs and optimizer.\n",
@@ -334,7 +323,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f970a995",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -344,7 +332,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3fe96a4a",
    "metadata": {},
    "source": [
     "### Visualize experiment\n",
@@ -355,7 +342,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5f13ab1e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -374,7 +360,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "777780e4",
    "metadata": {},
    "source": [
     "### Compare Experiments, Trials, and Trial Components in Amazon SageMaker Studio\n",
@@ -395,7 +380,6 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fa992be5",
    "metadata": {},
    "source": [
     "### Cleanup\n",
@@ -406,7 +390,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8672ca44",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -434,7 +417,6 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1da56a6c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -444,14 +426,12 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3cd76c89",
    "metadata": {},
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
-  "instance_type": "ml.t3.medium",
   "kernelspec": {
    "display_name": "Python 3 (TensorFlow 2.3 Python 3.7 CPU Optimized)",
    "language": "python",