Machine Learning – Python Programming: From Beginner to Intermediate

Machine Learning – Python Programming: From Beginner to Intermediate
Machine Learning – Python Programming: From Beginner to Intermediate
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 10.5 Hours | 2.99 GB

Python Programming: From Beginner to Intermediate is an essential training course for anyone who wants to begin learning Python. Using a Python IDE (integrated development environment) called iPython from Anaconda, the expert instructors in this course will lead you step-by-step through topics such as: functional language constructs, automated reports, website scraping, and natural language processing.

What am I going to get from this course?

  • Pick up programming even if you have NO programming experience at all
  • Write Python programs of moderate complexity
  • Perform complicated text processing – splitting articles into sentences and words and doing things with them
  • Work with files, including creating Excel spreadsheets and working with zip files
  • Apply simple machine learning and natural language processing concepts such as classification, clustering and summarization
  • Understand Object-Oriented Programming in a Python context
Table of Contents

01 - Introduction
02 - Coding is Like Cooking
03 - Anaconda & Pip
04 - Variables are Like Containers
05 - A List is a List
06 - Fun with Lists!
07 - Dictionaries & If-Else
08 - Don't Jump through Hoops - Use Loops
09 - Doing Stuff with Loops
10 - Everything in Life is a List - Strings as Lists
11 - Modules are Cool for Code-Reuse
12 - Our First Serious Program - Downloading a Webpage
13 - A Few Details - Conditionals
14 - A Few Details - Exception Handling in Python
15 - A File is Like a Barrel
16 - Auto-Generating Spreadsheets with Python
17 - Auto-Generating Spreadsheets - Download & Unzip
18 - Auto-Generating Spreadsheets - Parcing CSV Files
19 - Auto-Generating Spreadsheets with XLSXwriter
20 - Functions are Like Food Processors
21 - Argument Passing in Functions
22 - Writing Your First Function
23 - Recursion
24 - Recursion in Action
25 - How Would You Implement a Bank ATM
26 - Things You Can Do with Databases - I
27 - Things You Can Do with Databases - II
28 - Interfacing with Databases from Python
29 - SQLite Works Right out of the Box
30 - Manually Downloading the ZIP Files Required
31 - Build a Database of Stock Movements - I
32 - Build a Database of Stock Movements - II
33 - Build a Database of Stock Movements - III
34 - Objects are Like Puppies!
35 - A Class is a Type of Variable
36 - An Interface Drives Behavior
37 - Natural Language Processing with NLTK
38 - Natural Language Processing with NLTK - See It in Action
39 - Web Scraping with BeautifulSoup
40 - A Serious NLP Application - Text Auto-Summarization Using Python
41 - Auto-Summarize News Articles - I
42 - Auto-Summarize News Articles - II
43 - Auto-Summarize News Articles - III
44 - Machine Learning - Jump on the Bandwagon
45 - Plunging In - Machine Learning Approaches to Spam Detection
46 - Spam Detection with Machine Learning - Continued
47 - News Article Classification Using K-Nearest Neighbors
48 - News Article Classification Using Naive Bayes
49 - Code Along - Scraping News Websites
50 - Code Along - Feature Extraction from News Articles
51 - Code Along - Classification with K-Nearest Neighbors
52 - Code Along - Classification with Naïve Bayes
53 - Document Distance Using TF-IDF
54 - News Article Clustering with K-Means & TF-IDF
55 - Code Along - Clustering with K-Means