Data science and AI have been the force behind the rise of Python adoption .

According to the State of the Octoverse report, Python has beaten out Java to become the second most used language after JavaScript.

The growth of Python can be correlated with a wide range of tools and frameworks. The most notable ones are the surge of Jupyter Notebook, TensorFlow, and NLTK. Jupyter Notebook has risen over 100% YoY for last thee years. Besides, TensorFlow and NLTK were among the most popular projects, thereby increasing the number of contribution from Python users; TensorFlow was fifth in the number of contribution with 9.9k.

Siraj Raval shows off examples of machine learning apps from his students.

If you’re wondering about my stance on the recent controversies around Siraj, I recorded a Data Point about that.

Machine Learning powers almost every internet service we use these days, but it’s rare to find a full pipeline example of machine learning being deployed in a web app. In this episode, I’d like to present 5 full-stack machine learning demos submitted as midterm projects from the students of my current course. The midterm assignment was to create a paid machine learning web app, and after receiving countless incredible submissions, I’ve decided to share my favorite 5 publicly. I was surprised by how many students in the course had never coded before and to see them building a full-stack web app in a few weeks was a very fulfilling experience. Use these examples as a template to help you ideate on potential business ideas to make a positive impact in the world using machine learning. And if you’d like, be sure to reach out and support each of the students I’ve demoed here today in any way can you offer. They’ve been working their butts off. Enjoy!

Presentation notebook:

Corey Schafer explains how to use multiprocessing in Python.

In this Python Programming video, we will be learning how to run code in parallel using the multiprocessing module. We will also look at how to process multiple high-resolution images at the same time using a ProcessPoolExecutor from the concurrent.futures module. Let’s get started…

The code from this video can be found at: has posted a full 14 hour network penetration testing/ethical hacking in this full tutorial course for beginners.

This course teaches everything you need to know to get started with ethical hacking and penetration testing. You will learn the practical skills necessary to work in the field.

Throughout the course, you will develop your own Active Directory lab in Windows, make it vulnerable, hack it, and patch it. We’ll cover the red and blue sides. We’ll also cover some of the boring stuff like report writing :).

This course was originally live streamed weekly on Twitch and built from lessons learned in the previous week.

GitHub repo (for homework):

Course created by The Cyber Mentor.

Check out his YouTube channel:

Course Contents

  • (0:00) – Course Introduction/whoami
  • (6:12) – Part 1: Introduction, Notekeeping, and Introductory Linux
  • (1:43:45) – Part 2: Python 101
  • (3:10:05) – Part 3: Python 102 (Building a Terrible Port Scanner)
  • (4:23:14) – Part 4: Passive OSINT
  • (5:41:41) – Part 5: Scanning Tools & Tactics
  • (6:56:42) – Part 6: Enumeration
  • (8:31:22) – Part 7: Exploitation, Shells, and Some Credential Stuffing
  • (9:57:15) – Part 8: Building an AD Lab, LLMNR Poisoning, and NTLMv2 Cracking with Hashcat
  • (11:13:20) – Part 9: NTLM Relay, Token Impersonation, Pass the Hash, PsExec, and more
  • (12:40:46) – Part 10: MS17-010, GPP/cPasswords, and Kerberoasting
  • (13:32:33) – Part 11: File Transfers, Pivoting, Report Writing, and Career Advice has a two hour, ad-free tutorial on how to use TensorFlow 2.0 in this full course for beginners.

Course created by Tech with Tim. Check out his YouTube channel:

Course Contents

  • (0:00:00) What is a Neural Network?
  • (0:26:34) How to load & look at data
  • (0:39:38) How to create a model
  • (0:56:48) How to use the model to make predictions
  • (1:07:11) Text Classification (part 1)
  • (1:28:37) What is an Embedding Layer? Text Classification (part 2)
  • (1:42:30) How to train the model – Text Classification (part 3)
  • (1:52:35) How to saving & loading models – Text Classification (part 4)
  • (2:07:09) How to install TensorFlow GPU on Linux