NetworkChuck shows us how to optimize the Raspberry Pi for kids to learn Linux, coding, and Hacking.
We setup multi-user login, add user accounts, enable remote access from an ipad, and install Kali Linux hacking tools Yersinia and Ettercap.
deeplizard demonstrates how to use data augmentation on images using TensorFlow’s Keras API.
VIDEO SECTIONS
- 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
- 00:17 Introduction to Data Augmentation
- 01:32 Image Augmentation with Keras
- 08:16 Collective Intelligence and the DEEPLIZARD HIVEMIND
In this video, take a look at four new features in Python 3.9:
- new syntax for merging/updating dicts,
- native timezone support,
- the use of collection classes as opposed to the typing model for type support,
- removeprefix and removesuffix method for strings.
Time stamps:
- 00:00 – Intro
- 00:22 – Dict Merge/Update
- 03:33 – Native Timezones
- 06:22 – Collection Type Hints
- 08:48 – str.removeprefix
Time series are ubiquitous in real-world applications, but often add considerable complications to data science workflows. What’s more, most available machine learning toolboxes (e.g. scikit-learn) are limited to the tabular setting, and cannot easily be applied to time series data.
In this tutorial, you’ll learn how to apply common machine learning techniques to time series and how to extend available toolkits. This is a beginner-friendly tutorial: we assume familiarity with scikit-learn, but no prior experience with time series.
To start, you’ll learn how to distinguish between different kinds of temporal data and associated learning tasks, such as forecasting and time series classification. You’ll then learn how to solve these tasks with machine learning techniques specific to time series data.
Simplilearn explains OOP in the context of Python.
Python is an Object Oriented Programming language that allows you to create different classes and objects. This Python Classes and Objects tutorial will help you understand a class in Python and how to use Python classes. You will get an idea about an object in Python, how to declare and use objects in Python, and perform a simple demo.
In this episode, Mandy from deeplizard will be building on what we’ve learned about MobileNet combined with the techniques we’ve used for fine-tuning to fine-tune MobileNet for a custom image data set using TensorFlow’s Keras API.
In this deeplizard episode, learn how to prepare and process our own custom data set of sign language digits, which will be used to train our fine-tuned MobileNet model in a future episode.
VIDEO SECTIONS
- 00:00 Welcome to DEEPLIZARD – Go to deeplizard.com for learning resources
- 00:40 Obtain the Data
- 01:30 Organize the Data
- 09:42 Process the Data
- 13:11 Collective Intelligence and the DEEPLIZARD HIVEMIND
Computer Science explains how to use Python and Machine Learning to predict stock prices.
Computerphile explains why laziness may be a virtue (in programming).
Professor Thorsten Altenkirch on how you can use the ‘yield’ to compute certain things “on demand”
Learn all about Data Structures in this lecture-style course from freeCodeCamp.org
You will learn what Data Structures are, how we measure a Data Structures efficiency, and then hop into talking about 12 of the most common Data Structures which will come up throughout your Computer Science journey.
Course Contents
- (00:00) Introduction
- (01:06) Timestamps
- (01:23) Script and Visuals
- (01:34) References + Research
- (01:56) Questions
- (02:12) Shameless Plug
- (02:51) What are Data Structures?
- (04:36) Series Overview
- (06:55) Measuring Efficiency with BigO Notation
- (09:45) Time Complexity Equations
- (11:13) The Meaning of BigO
- (12:42) Why BigO?
- (13:18) Quick Recap
- (14:27) Types of Time Complexity Equations
- (19:42) Final Note on Time Complexity Equations
- (20:21) The Array
- (20:58) Array Basics
- (22:09) Array Names
- (22:59) Parallel Arrays
- (23:59) Array Types
- (24:30) Array Size
- (25:45) Creating Arrays
- (26:11) Populate-First Arrays
- (28:09) Populate-Later Arrays
- (30:22) Numerical Indexes
- (31:57) Replacing information in an Array
- (32:42) 2-Dimensional Arrays
- (35:01) Arrays as a Data Structure
- (42:21) Pros and Cons
- (43:33) The ArrayList
- (44:42) Structure of the ArrayList
- (45:19) Initializing an ArrayList
- (47:34) ArrayList Functionality
- (49:30) ArrayList Methods
- (50:26) Add Method
- (53:57) Remove Method
- (55:33) Get Method
- (55:59) Set Method
- (56:57) Clear Method
- (57:30) toArray Method
- (59:00) ArrayList as a Data Structure
- (1:03:12) Comparing and Contrasting with Arrays
- (1:05:02) The Stack
- (1:05:06) The Different types of Data Structures
- (1:05:51) Random Access Data Structures
- (1:06:10) Sequential Access Data Structures
- (1:07:36) Stack Basics
- (1:09:01) Common Stack Methods
- (1:09:45) Push Method
- (1:10:32) Pop Method
- (1:11:46) Peek Method
- (1:12:27) Contains Method
- (1:13:23) Time Complexity Equations
- (1:15:28) Uses for Stacks
- (1:18:01) The Queue
- (1:18:51) Queue Basics
- (1:20:44) Common Queue Methods
- (1:21:13) Enqueue Method
- (1:22:20) Dequeue Method
- (1:23:08) Peek Method
- (1:24:15) Contains Method
- (1:25:05) Time Complexity Equations
- (1:27:05) Common Queue Uses
- (1:28:16) The Linked List
- (1:31:37) LinkedList Visualization
- (1:33:55) Adding and Removing Information
- (1:41:28) Time Complexity Equations
- (1:44:26) Uses for LinkedLists
- (1:47:19) The Doubly-LinkedList
- (1:48:44) Visualization
- (1:50:56) Adding and Removing Information
- (1:58:30) Time Complexity Equations
- (1:59:06) Uses of a Doubly-LinkedList
- (2:00:21) The Dictionary
- (2:01:15) Dictionary Basics
- (2:02:00) Indexing Dictionaries
- (2:02:40) Dictionary Properties
- (2:05:53) Hash Table Mini-Lesson
- (2:13:26) Time Complexity Equations
- (2:16:39) Trees
- (2:16:55) Introduction to Hierarchical Data
- (2:18:54) Formal Background on the Tree
- (2:20:03) Tree Terminology and Visualization
- (2:25:08) Different types of Trees
- (2:28:07) Uses for the Tree
- (2:29:00) Tries
- (2:29:50) Trie Basics
- (2:30:41) Trie Visualization
- (2:34:33) Flagging
- (2:35:15) Uses for Tries
- (2:38:25) Heaps
- (2:38:51) Heap Basics
- (2:39:19) Min-Heaps
- (2:40:07) Max-Heaps
- (2:40:59) Building Heaps
- (2:44:20) Deleting from Heaps
- (2:46:00) Heap Implementations
- (2:48:15) Graphs
- (2:49:25) Graph Basics
- (2:52:04) Directed vs. Undirected Graphs
- (2:53:45) Cyclic vs. Acyclic Graphs
- (2:55:04) Weighted Graphs
- (2:55:46) Types of Graphs
- (2:58:20) Conclusion
- (2:58:43) Shameless Plug