This repo is used to store all folders that were used for educational purposes. Folders were created to store code that I created for a particular class and code I created from additional resources I used outside of the classroom.

**Some of the code was made when I first started programming. As a result, comments may not have been made properly; however, all of the code is working. I wanted to keep a record of all of the work I have done up to this point.

1. Python Programming

    This is one of my biggest folders and one that I started several years ago. This folder
    has all of my Python code that was created during the time I've spent learning about
    Python. The folder has basic to data structures implementation. I studied Python from 
    Coursera, UHCL and I most recently tried completing a 10 hour boot camp in November 
    2019 from Udemy. I tried most of the practice problems and completed the 2 capstone 
    projects. I did a tic tac toe and black jack game. 
   

2. Java Programming

    Java was the first language that I learned. The code I have written is several 
    years worth of learning. I started learning on my own by reading Building Java Programs:
    A Back to Basics Approach (3rd edition). I have completed nearly all of the practice
    problems from every chapter. I did the practice problems using a website hosted by the
    University fo Washington at https://practiceit.cs.washington.edu/problem/list I also
    wrote the code on Intellij. 
    
    In this folder there is also a DataStructures folder where I followed a course from
    UC Berkeley, CS 61B at https://sp19.datastructur.es. I did most of work related to 
    data structures, professor Josh Hug is an amazing instructor. His live coding lectures
    are great because a lot of the time he goes back and forth between Python and Java. This
    course is ideal for students that want to keep their skills sharp in Java and Python. 
   

3. Java Script

    I recently started learning JS, during Fall semester 2019. My goal is to use JS in my 
    project(s). I started working on a website earlier in the Fall semester in 2019 for a small
    restaurant in Everett Washington. I have been learning JS by building small games and
    accessing elements via DOM manipulation. 
   

4. Machine Learning

    I find machine learning to be very interesting and most of it was self-taught by reading
    books and going through online tutorials. I also took a few tutorials to learn NumPy and
    Pandas, since then I have just kept on expanding my knowledge in Machine Learning. I also 
    took a course at UHCL, where I built, from scratch, the PLA and Linear Regression Models 
    with gradient descent to predict stock prices. Under my projects section I have uploaded 
    the source code. 
   

5. Data Analysis Visualization

    For some time now, I have been interested in learning more about Machine Learning and I
    started learning on my own in the summer of 2019. I created this folder to put code 
    related to Machine Learning like Numpy, Pandas and plotting. I am using Anaconda,
    Spyder, and many scientific modules to learn about Machine Learning.
   

   For example, I created the folder [Numpy Pandas](https://github.com/gonzalob24/ Learning_Central/tree/master/Data_Analysis_Visualization/Numpy_Pandas) to put code that I created using Python when I started learning about Numpy and pandas.

   The folder [Stats Basic](https://github.com/gonzalob24/Learning_Central/tree/master/ Data_Analysis_Visualization/Stats_Basics) has a few Python scripts with information about statistics, like Binomial Distribution, Continuous and Discrete Uniform Distributions, normal and poisson Distribution.

   Working With Data, has a few Python files about dealing with data. Reading and saving files. Merging dataframes, concatenating, grouping, joining and learning to use a few functions like apply and reshaping matrices.

   [Data Visualization](https://github.com/gonzalob24/Learning_Central/tree/master/ Data_Analysis_Visualization/Data_Visualization), this folder has learning material about plotting data. I constantly use this folder to reference code to use on other projects. Some of the plots I have created are histograms, kde plots, heat maps, regression such as lmplots and regplots. I may update this file with new plots styles or have links to code that I use elsewhere in current and future projects.

6. C Programming

    Folder was created during Fall semester 2018 for C Programming class that I took at 
    UHCL. There are a few assignments that I created while I was enrolled in the class.
    I did not do additional projects with C language. I know and recoginze basic syntax
    like creating variables, arrays, for loops, while loops, switch, input and output, 
    creating functions and returning values from functions. 
   

7. Coding Interviews

   This folder was created in the Spring of 2020. I am putting coding interview questions 
   that I found in various sources like Cracking the Coding Interview, Kattis Problems and
   LeetCode. I will continue adding to this folder during times when I am preparing for
   an interview. The main languages I am using to code the practice problems are Python
   and Java. In the near future I may switch Java for JavaScript.
   

8. GPIOZero Pi3

    In the summer of 2019 I was curious about the Raspberry Pi 3 B+ so I decided to 
    learn about connecting external devices to the GPIO Pins. I created a few LED scripts
    using Python on the Raspberry Pi. Connected Push Buttons, Motors and a Camera. 
   

   Lessons Learned:

    Some of the biggest lessons I learned from using the Raspberry Pi was establishing an
    SSH connection using Linux and iMac. I also learned to create scripts to control
    external device. I simulated how traffic lights work in the real world with 
    TrafficLights.py and TrafficLights2.py
   

9. Image Processing

    This folder was also created in the summer of 2019 at the same time as the GPIOZero Pi3 		folder, to learn about image processing. I felt that knowing basic information about 		manipulating images with erosion, thresholding and edge detection would be useful when 
    learning about Machine Language.