{"id":16499197,"url":"https://github.com/hardbyte/python-ml-tut","last_synced_at":"2026-01-31T10:02:27.904Z","repository":{"id":27006236,"uuid":"30470314","full_name":"hardbyte/python-ml-tut","owner":"hardbyte","description":"Introduction to Machine Learning with Python","archived":false,"fork":false,"pushed_at":"2015-02-09T01:32:26.000Z","size":2440,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-10-12T05:07:23.793Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/hardbyte.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-02-07T21:08:41.000Z","updated_at":"2015-02-07T21:08:41.000Z","dependencies_parsed_at":"2022-06-26T04:45:00.508Z","dependency_job_id":null,"html_url":"https://github.com/hardbyte/python-ml-tut","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/hardbyte/python-ml-tut","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hardbyte%2Fpython-ml-tut","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hardbyte%2Fpython-ml-tut/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hardbyte%2Fpython-ml-tut/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hardbyte%2Fpython-ml-tut/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hardbyte","download_url":"https://codeload.github.com/hardbyte/python-ml-tut/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hardbyte%2Fpython-ml-tut/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28937813,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-31T08:53:31.997Z","status":"ssl_error","status_checked_at":"2026-01-31T08:51:38.521Z","response_time":128,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-11T14:51:30.796Z","updated_at":"2026-01-31T10:02:27.887Z","avatar_url":"https://github.com/hardbyte.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Getting Started\n\n## Download Python 3.4\n\nInstall the Anaconda Python distribution from [continuum.io](http://continuum.io/downloads#py34).\nBe sure to click **I WANT PYTHON 3.4**. Direct download links are:\n\n- [Anaconda Python 3.4 - Windows 64](http://repo.continuum.io/anaconda3/Anaconda3-2.1.0-Windows-x86_64.exe)\n- [Anaconda Python 3.4 - OSX](http://repo.continuum.io/anaconda3/Anaconda3-2.1.0-MacOSX-x86_64.pkg)\n\n\n## Start IPython Notebook\n\nFind the Anaconda **Launcher** and launch:\n\n    ipython notebook\n\nYour browser should open up to http://localhost:8888 and show your home directory.\nFind your way to the directory where you downloaded and unzipped the python-ml-tut\n\n\nIf you run into trouble, ask one of the friendly tutors. Or start reading the notebook in \nreadonly mode at [nbviewer.ipython.org](http://nbviewer.ipython.org/github/hardbyte/python-ml-tut/blob/master/Intro%20to%20python.ipynb)\n\n## Begin the tutorial\n\nOpen the `Intro to python.ipynb` Notebook and start working through the exercises.\n\n\n## Already have Python 3.4?\n \nJust make sure you have all the requirements installed for this tutorial by running:\n\n    pip install -r requirements.txt\n\n# Python Quickstart\n\n# New to Python?\n\n## Resources\n\n- [Learn Python The Hardway](http://learnpythonthehardway.org/book/)\n- [Online Python Interactive Debugger](http://people.csail.mit.edu/pgbovine/python/)\n- [Dive into Python 3](http://getpython3.com/diveintopython3/)\n- [Interactive Python](http://interactivepython.org/courselib/static/thinkcspy/index.html)\n\n## Intro to Python Cheatsheet\n\nLaunch the IPython QT console and try run (and understand) these commands:\n\n```python\n# This is a comment line\n# numbers and variables\nage = 26\npi = 3.14159\n\n# strings and methods\ns = 'Hugh F Durrant-Whyte'\n\n# Strings have a method `split` which returns a list of strings split by whitespace\ntokens = s.split()\nfirstName = tokens[0]\nmiddleName = tokens[1]\nlastName = tokens[2]\ns2 = firstName + ' ' + middleName + ' ' + lastName\n\n# 'if' statement - indentation matters\nif s == s2:\n    print('yes the strings are equal')\nelse:\n    print('no')\n\n# if statements can also be inline\nanswer = 'yes' if s == s2 else 'no' \n\n# list (mutable ordered sequence)\nbeatles = ['John', 'Paul', 'George']\nbeatles.append('Ringo')\nprint(beatles)\nprint('Ringo' in beatles)\n\n\n# 'for' loop - indentation matters\n# Note that name is defined inside the for loop\nfor name in beatles:\n    print('Hello ' + name)\n\n# Iterating over a range of numbers is easy\n# range has the following arguments (start, stop, step) where stop isn't included\nfor number in range(2, 10, 2):\n    print(number)\n\n# tuple (immutable ordered sequence)\nages = (18, 21, 28, 21, 22, 18, 19, 34, 9)\n\n# Note you can't change the contents of a tuple\n\n# set (mutable, unordered, no duplicates)\nuniqueAges = set(ages)\nuniqueAges.add(18) # already in set, no effect\nuniqueAges.remove(21)\n\n\n# testing set membership (very fast)\nif 18 in uniqueAges:\n    print('There is an 18-year-old present!')\n\n# sorting a list\nsorted(beatles) # returns a new sorted list\nbeatles.sort() # in-place - changes beatles list\n\n# Sorting a set returns a list\norderedUniqueAges = sorted(uniqueAges)\n\n# There is no guaranteed order when iterating over a set\nfor thisAge in uniqueAges:\n    print(thisAge)\n\n# Instead iterate over the sorted set:\nfor age in sorted(uniqueAges):\n    print(age)\n\n# dict - mapping unique keys to values\nnetWorth = {}\nnetWorth['Donald Trump'] = 3000000000\nnetWorth['Bill Gates'] = 58000000000\nnetWorth['Tom Cruise'] = 40000000\nnetWorth['Joe Postdoc'] = 20000\n\n# Access the value associated with a key\nprint(netWorth['Donald Trump'])\n\n# iterating over a dict gives keys\nfor personName in netWorth:\n    print(personName + \" is worth: \", end='')\n    print(netWorth[personName])\n\n# You can also iterate over key-value pairs:\nfor (person, worth) in netWorth.items():\n    if worth \u003c 1000000:\n        print('haha ' + person + ' is not a millionaire')\n\n# testing dict membership is the same as with a set\nif 'Tom Cruise' in netWorth:\n    print('show me the money!')\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhardbyte%2Fpython-ml-tut","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhardbyte%2Fpython-ml-tut","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhardbyte%2Fpython-ml-tut/lists"}