Merge my changes to the master branch

assignment/a0/a0.ipynb

@@ -3,7 +3,7 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "kDFiCs_0MaeI"
+        "id": "lqbcQ5cWLvqY"
       },
       "source": [
         "# Assignment 0\n",
@@ -21,10 +21,29 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "Rk5s0520MaeO",
-        "outputId": "c75272ad-f95a-4eb6-8a1c-b1b9d1e55cfc"
+        "id": "CEbay1iyLvqZ",
+        "outputId": "8b5f4604-57c5-4024-c1bf-e0ed703a5954"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "numpy version 1.26.4 is \n",
+            "OK\n",
+            "matplotlib version 3.7.1 is \n",
+            "OK\n",
+            "pandas version 2.1.4 is \n",
+            "OK\n",
+            "nltk version 3.8.1 is \n",
+            "OK\n",
+            "keras version 3.4.1 is \n",
+            "OK\n",
+            "tensorflow version 2.17.0 is \n",
+            "OK\n"
+          ]
+        }
+      ],
       "source": [
         "# Version checks\n",
         "import importlib\n",
@@ -49,18 +68,18 @@
         "           if version_greater_equal(m.__version__, min_version)\n",
         "           else \"out-of-date. Please upgrade!\")\n",
         "\n",
-        "version_check(\"numpy\", \"1.26.4\")\n",
-        "version_check(\"matplotlib\", \"3.7.1\")\n",
-        "version_check(\"pandas\", \"2.1.4\")\n",
-        "version_check(\"nltk\", \"3.8.1\")\n",
-        "version_check(\"keras\", \"3.4.1\")\n",
-        "version_check(\"tensorflow\", \"2.17.0\")"
+        "version_check(\"numpy\", \"1.21.5\")\n",
+        "version_check(\"matplotlib\", \"3.5.2\")\n",
+        "version_check(\"pandas\", \"1.4.4\")\n",
+        "version_check(\"nltk\", \"3.7\")\n",
+        "version_check(\"keras\", \"2.11.0\")\n",
+        "version_check(\"tensorflow\", \"2.11.0\")"
       ]
     },
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "MJeLTePaMaeT"
+        "id": "1RdTZKXoLvqa"
       },
       "source": [
         "## TensorFlow\n",
@@ -81,10 +100,19 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "Yeo7loI7MaeU",
-        "outputId": "abab1260-7170-4b11-892f-97cd7a58cadb"
+        "id": "pudPWEYOLvqb",
+        "outputId": "b05f6256-1087-4db2-c596-93f116973e5a"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Hello, TensorFlow!\n",
+            "42\n"
+          ]
+        }
+      ],
       "source": [
         "import tensorflow as tf\n",
         "\n",
@@ -99,7 +127,7 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "6tpeOZp4MaeV"
+        "id": "OH2xbX5eLvqb"
       },
       "source": [
         "## NLTK\n",
@@ -125,10 +153,20 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "WibuBpFrMaeW",
-        "outputId": "100790cd-1089-408b-800a-1f8094b84935"
+        "id": "LQAbspMQLvqb",
+        "outputId": "dbdbaf39-dd28-47a3-f737-4be21241d610"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
+            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
+            "[nltk_data] Downloading package reuters to /root/nltk_data...\n"
+          ]
+        }
+      ],
       "source": [
         "import nltk\n",
         "assert(nltk.download('punkt'))\n",
@@ -138,7 +176,7 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "TvBDxW_LMaeX"
+        "id": "HpQR2oiALvqb"
       },
       "source": [
         "Now we can look at a few sentences. Expect to see:\n",
@@ -156,10 +194,21 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "_GweB4zRMaeX",
-        "outputId": "2faaf18e-03d1-4936-bfcd-9e33880e98f2"
+        "id": "MJFnYc2tLvqb",
+        "outputId": "e60455ba-dc05-4961-eafa-7c3bf8de3368"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "ASIAN EXPORTERS FEAR DAMAGE FROM U . S .- JAPAN RIFT Mounting trade friction between the U . S . And Japan has raised fears among many of Asia ' s exporting nations that the row could inflict far - reaching economic damage , businessmen and officials said .\n",
+            "\n",
+            "They told Reuter correspondents in Asian capitals a U . S . Move against Japan might boost protectionist sentiment in the U . S . And lead to curbs on American imports of their products .\n",
+            "\n"
+          ]
+        }
+      ],
       "source": [
         "from nltk.corpus import reuters\n",
         "# Look at the first two sentences\n",
@@ -171,7 +220,7 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "WjYOd3vQMaeY"
+        "id": "u71rOmTfLvqb"
       },
       "source": [
         "NLTK also includes a sample of the [Penn treebank](https://www.cis.upenn.edu/~treebank/), which we'll be using later in the course for parsing and part-of-speech tagging. Here's a sample of sentences, and an example tree. Expect to see:\n",
@@ -195,10 +244,35 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "ONFIsI-aMaeZ",
-        "outputId": "4974f6c5-9f5d-4baf-852b-827e4b2bd679"
+        "id": "QM10J7JiLvqb",
+        "outputId": "618f1c11-4b95-4d6a-86c6-1e9f5b0be33e"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[nltk_data] Downloading package treebank to /root/nltk_data...\n",
+            "[nltk_data]   Unzipping corpora/treebank.zip.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "The top money funds are currently yielding well over 9 % .\n",
+            "\n",
+            "(S\n",
+            "  (NP-SBJ (DT The) (JJ top) (NN money) (NNS funds))\n",
+            "  (VP\n",
+            "    (VBP are)\n",
+            "    (ADVP-TMP (RB currently))\n",
+            "    (VP (VBG yielding) (NP (QP (RB well) (IN over) (CD 9)) (NN %))))\n",
+            "  (. .))\n"
+          ]
+        }
+      ],
       "source": [
         "assert(nltk.download(\"treebank\"))  # should return True if successful, or already installed\n",
         "print(\"\")\n",
@@ -214,7 +288,7 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "OcQzQGo9Maea"
+        "id": "F1uSzJwALvqc"
       },
       "source": [
         "We can also look at the [Europarl corpus](http://www.statmt.org/europarl/), which consists of *parallel* text - a sentence and its translations to multiple languages. You should see:\n",
@@ -231,10 +305,31 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "id": "MGOrVrQtMaeb",
-        "outputId": "1df61c59-9bae-4b6c-e965-6af6d1683646"
+        "id": "1T6fO8CWLvqc",
+        "outputId": "872eeb95-a35d-4d09-e4a8-c34081cc4915"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "[nltk_data] Downloading package europarl_raw to /root/nltk_data...\n",
+            "[nltk_data]   Unzipping corpora/europarl_raw.zip.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n",
+            "ENGLISH: Resumption of the session I declare resumed the session of the European Parliament adjourned on Friday 17 December 1999 , and I would like once again to wish you a happy new year in the hope that you enjoyed a pleasant festive period .\n",
+            "\n",
+            "FRENCH: Reprise de la session Je déclare reprise la session du Parlement européen qui avait été interrompue le vendredi 17 décembre dernier et je vous renouvelle tous mes vux en espérant que vous avez passé de bonnes vacances .\n",
+            "\n",
+            "SPANISH: Reanudación del período de sesiones Declaro reanudado el período de sesiones del Parlamento Europeo , interrumpido el viernes 17 de diciembre pasado , y reitero a Sus Señorías mi deseo de que hayan tenido unas buenas vacaciones .\n"
+          ]
+        }
+      ],
       "source": [
         "assert(nltk.download(\"europarl_raw\"))  # should return True if successful, or already installed\n",
         "print(\"\")\n",
@@ -253,7 +348,7 @@
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "f6aRtMyvMaeb"
+        "id": "fnAu--ZbLvqc"
       },
       "outputs": [],
       "source": []
@@ -276,12 +371,12 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.11.4"
+      "version": "3.9.13"
     },
     "colab": {
       "provenance": []
     }
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}

assignment/a0/answers

@@ -8,13 +8,13 @@
 #      course policy, while still being confident everyone has read the syllabus.
 
 # Replace the next two lines with your name.
-last_name: Lastname
-first_name: FirstName
+last_name: Ramirez
+first_name: Jeremy
 
 # Replace the next line with your Berkeley email address.
 # We use it to give you access to the grading sheet.  It *must* be @berkeley.edu.
 # See the assignment instructions on how to get one if you don't have one already!
-email: placeholder@berkeley.edu
+email: jeremy.ramirez@berkeley.edu
 
 ## Read the following thoroughly:
 #  - syllabus/README.md
@@ -26,33 +26,29 @@ email: placeholder@berkeley.edu
 
 main_components:
   - Term project
-  - Midterm examination
   - Assignments
   - Participation
-  - Final examination
 
 # 2.  What are the three graded components of the project?
 # (Delete the incorrect answers.)
 
 project_components:
   - Proposal
-  - Presentation
-  - Office hour proposal discussions
   - Milestone
   - Final report
 
 # 3. How many late days can you use over the semester?
 # (Replace the 0 with the right answer.)
-late_days: 0
+late_days: 5
 
 # 4. How many late days can you use on a single assignment?
 # (Replace the 0 with the right answer.)
-late_days_per: 0
+late_days_per: 2
 
 # 5. If you run out of late days, and hand it in 12 hours after the deadline,
 #    how much is your grade reduced on that assignment?
 # (Replace the 0 with the right answer.)
-late_penalty: 0%age points
+late_penalty: 10%age points
 
 # 7. 48 hours after the deadline, what is the maximum assignment grade?
 # (Replace the 0 with the right answer.)
@@ -62,36 +58,25 @@ past_hard_deadline_grade: 0
 # (Delete the incorrect answers.)
 general_questions:
   - Public post on Ed Discussion
-  - Private post on Ed Discussion addressed to all instructors so they can load balance
-  - Private post on Ed Discussion addressed to your live session instructor
-  - Instructor email list
-  - Your live session instructor's berkeley email address
 
 # 9. Which of the following are appropriate places to ask questions that cannot be made
 #    public (e.g. ones that contain assignment solutions?)
 # (Delete the incorrect answers.)
 private_questions:
-  - Public post on Ed Discussion
   - Private post on Ed Discussion addressed to all instructors so they can load balance
   - Private post on Ed Discussion addressed to your live session instructor
-  - Instructor email list
-  - Your live session instructor's berkeley email address
 
 # 10. If you need something beyond the late day policy, what do you do?
 # (Delete the incorrect answers.)
 beyond_late_days:
   - Email the instructor mailing list, and cc student support as early as possible,
     even if you aren't completely sure you'll need anything.
-  - Ask on Ed Discussion
-  - Wait until the most dire consequences are upon you before mentioning anything
 
 # 11. Where do you find out which async to watch each week?
 # (Delete the incorrect answers.)
 async_source:
   - The "Async to watch" column in the syllabus
   - Watch "Unit x" while preparing for "Week x"'s live session.
-  - Ask on Ed Discussion
-  - I don't watch async.
 
 # 12. This course isn't known as a super easy class and I should be cautious about taking it
 #     in conjunction with:
@@ -101,12 +86,23 @@ competing_worries:
   - Capstone
   - MIDS 261
 
-# 13. I would rather:
+# 13. The grade distribution in this course has historically been
+# approximately (despite most students working really hard!):
+# (Replace the 0s with the correct values.)
+grade_A: 25%
+grade_A-: 15%
+grade_B+: 30%
+grade_B: 20%
+
+# 14. I would rather:
 # (Keep the one you agree with most.. no right answer here, this is us experimenting with the course and appreciate your feedback!)
 logistics_approach:
   - Spend the first live session going over this in detail
-  - Read it on my own, do this quiz, and spend live session time on course material, knowing I can ask questions on Ed Discussion and in Live Session as necessary
 
-# 14. "But I really wanted to say something more nuanced on the previous question!"
+# 15. "But I really wanted to say something more nuanced on the previous question!"
 #     Here's your chance!
-additional_logistics_comments: Put that text here (after the colon)!
+additional_logistics_comments: None
+<<<<<<< HEAD
+
+=======
+>>>>>>> 4395ddd9a7bc61f15a0132b289431cd60de67a80