Kategoriler
C
Functions
Function Prototypes
Local Variables
Global Variables
Static Variables
Pointers
Passing Pointers as Parameters
Structures
Passing Struct Pointers to Functions
Arrays
Passing Arrays to Functions
Struct Arrays
Strings
Dynamic Memory, malloc(), free()
Dynamic Memory, realloc(), calloc()
typedef
enum
Pointer Arithmetic
Command Line Arguements
Multidimensional Arrays
Type Casting
Void Pointers, NULL Pointers
Multifile Projects
Preprocessors, #include, #define, #if, #ifdef
Dynamic 2D Array with Double Pointer
Pointers to Functions
Variable Argument Lists
FILE Keyword
fopen(), fclose()
printf(), fprintf()
scanf(), fscanf()
gets(), fgets()
getc(), fgetc(), getchar()
puts(), fputs()
putc(), fputc(), putchar()
fseek(), rewind(), ftell()
ungetc()
fread(), fwrite()
feof(), ferror(), perror(), clearerr()
rename(), remove()
tmpfile(), tmpnam()
setbuf(), setvbuf(), fflush()
strlen()
strcmp(), strncmp()
strcat(), strncat()
strchr(), strrchr()
strcpy(), strncpy()
strspn(), strcspn()
strstr()
strtok()
Math Library
sin(), cos(), tan()
asin(), acos(), atan()
sqrt()
difftime()
asctime(), ctime()
localtime()
time()
strftime()
rand()
srand()
Random Numbers Within a Given Range
Linear Search
Binary Search
Bubble Sort
Recursive Bubble Sort
Insertion Sort
Selection Sort
Quick Sort
Merge Sort
Hash Table
Hash Table with Struct
Comparison of Sorting Algorithms
Linked List
Stack
Queue
Graph
Binary Tree
Bank Customer Management Project
Calendar App
Snake Game
Contact Management Application

C++
Hello World in CPP
Working with Strings
Looping and Counting
Working with Batches of Data
Organizing Program and Data
Using Sequential Containers and Analyzing Strings
Using Library Algorithms
Using Associative Containers
Writing Generic Functions
Defining New Types
Managing Memory and Low Level Data Structures
Defining Abstract Data Types
Making Class Objects Act Like Values
Using Inheritance

CSS
Introduction to CSS
Color
Text in CSS
Boxes
Lists, Tables, Forms
Layouts
Images

Data Mining
Definition of Problem
Preparing Data
Regression
Measuring Performance of Regression
Classification
Measuring Performance of Classification
Unsupervised Learning, Clustering
Partitioning Based Methods
Hierarchical Methods
Testing and Validation
Data Analysis, Python, NumPy
Data Analysis, Python, Pandas

Django
Installiation and Settings
Starting an Application
Customizing Admin Panel
Using ORM
URL Structure
Static Files
Inheritance, extends
Adding Navbar and About Page
Dynamic URL and Sending Objects to HTML
URLs for Applications
Register Form, Saving Users
Messages in Django
Login Page
Crispy Forms
Logout, Session Control, Navbar
Dashboard
Adding Articles
Articles in Dashboard
Article Detail
404 Page
Bootstrap Files, collectstatic
CKEditor and Code Sharing
File Upload
Updating and Deleting Articles
Articles Page, Adding Code Snippet
Filters, Read More, Dynamic Href
Searching the Articles
Creating and Showing Comments

Flask
Introduction and URL Structure
HTML Templates
Template Inheritance, Blocks
Creating Navbar with Bootstrap
Conditions, If-Else, Loops
Dynamic URL Creation
Database Connection, flask-mysqldb
wtForms, Register Form
GET, POST, Register Page
Flash Messages
Login, Login Page
Session
Articles, Dashboard
CKEditor
Page for Articles
Dynamic URL for Articles
Updating, Deleting Articles
Searching Articles
ORM, SQLite, Installation
Interface of To-Do App
ORM, Adding, Deleting, Updating Data
To-Do App Final
User Login Control for Functions

HTML
Structure
Text
Creating Lists
Links
Images in HTML
Tables
Forms
Extra
Flash, Audio, Video

Java
Fonksiyon Kullanımı
Getter, Setter Methodlar ve This
Constructors
Inheritance, Super, Override
Polymorphisim, instanceof
Kart Oyunu
for-each Loop
ArrayLists
Autoboxing, Unboxing
String Class, length, charAt, startsWith, endsWith
Strings, indexOf, LowerUpperCase, ValueOf
LinkedLists
Interfaces
Static Keyword
Non-static Inner Classes
Static Inner Classes
Local Inner Classes
Anonymous Inner Classes, abstract Keyword
Generic Class
Generic Method
Access Modifiers
HashMap, LinkedHashMap, TreeMap
HashSet, LinkedHashSet, TreeSet
hashCode(), equals()
HashMap ile Karakter Frekansı
Comparable, CompareTo
Comparator, Compare
Vector, Stack
Iterator vs ListIterator
Iterable Interface, Creating Own Iterable Class
PriorityQueue
Using LinkedList as Queue
Exception Handling, Try, Catch, Finally
Exception Handling, Throw, Throws
Exception Handling, Creating Own Exception Classes
FileInputStream, FileOutputStream
FileWriter
Try With Resources
FileReader
BufferedReader, BufferedWriter
Serialization, ObjectOutputStream
Serialization, ObjectInputStream
Serialization, Arrays and Collections
Serialization, Transient
Creating Threads, Extending Thread Class
Creating Threads, Implementing Runnable Interface
Creating Threads, Anonymous Thread Class
Join, Synchronized
Multiple Locks
ThreadPool, ExecutorService
BlockingQueue, ProducerConsumer
wait, notify
ProducerConsumer with wait, notify
ReentrantLock, Condition Class, await, signal
DeadLock, tryLock
Callable, Future, Return from Threads
Interruptions
Database Connection
Database Connection, Commit, RollBack
Draw App
GUI, Dynamic Search
GUI, Graphics
GUI, JColorChooser, JFileChooser
GUI, ProgessBar
Workers App
Space Game
Bank Customer Management Project in Java
Pong Game
Snake Game in Java

Javascript
Introduction, Variables, Objects
Values
Operators
Booleans
Numbers
Strings in JavaScript
Statements
Exception Handling
Functions in JavaScript
Objects and Inheritance
Arrays in Javascript
Regular Expressions
Dates
Math

MATLAB
Basic Math and Matrix Operations
Elements of Matrices and String Arrays
MATLAB Tips
Input, Output
Variables
Conditions
Loops
Loop Examples
File Handling, Excel
File Handling, Txt
Functions in MATLAB
linspace(), datetime(), isweekend(), findpeaks()
Math, Matrix Functions
Symbolic Numbers, syms
assumptions(), assume(), assumeAlso()
Equation Solving, numden, expand, horner, divisors
Equation Solving, solve()
Graphs in MATLAB
File and Folder Operations
Image Processing, Introduction, RGB
Image Processing, map, load trees
Image Processing, Broken Candy Project
Image Processing, Coin Area Project
Image Processing, Plane Project
Image Processing, Finding Circles
Image Processing, Finding Circles - 2
Artificial Neural Networks, Fitting
Computer Vision, Plate Recognition Project

MIPS
Registers
Hello World in MIPS
Printing Integers, Chars, Floatings, Strings
Load Immidiate, Load Adress, li, la
Adding and Subtracting Integers
Multiplication and Division with Integers
Functions in MIPS
Function Arguments
Taking Inputs from User
If Statements
Shifting Operations
For Loop
While Loop
Arrays, Load Word, Store Word
Floating Point Arithmetic
Bit Manipulation
Instruction Reference

Machine Learning
Preprocessing, Data Import, Missing Values
Data, Encoding
Normalization, Standardization, train_test_split
Simple Linear Regression
Multiple Linear Regression, Preprocessing
MLRegression, Fitting, Backward Elimination
Polynomial Regression
Support Vector Regression
Decision Tree Regression
Random Forest
Metrics
Logistic Regression
K Neirest Neighborhood
Support Vector Machine
Naive Bayes
Decision Tree Classifier
Random Forest Classifier
Visualization - 3D Visualization
Visualization - Comparison of Classifiers
Iris - Classification
Iris - Classification with Visualization

OpenCV
Introduction and Installiation
Reading and Writing Images
Reading, Writing Videos and Accessing Camera
Drawing Shapes, Line, Circle, Rectangle
Paint Application
Changing Color with Trackbar
Combining Two Images, addWeighted()
Sliding Images
Rotating Images
Converting Images to Grayscale
Scaling, Resizing
Drawing Polygons
Image Pyramids, Cropping
Brightness Control
Bitwise Operations
Blurring
Denoising
Sharpening
Image Thresholding
Adaptive Thresholding
Morphological Transformations
Detecting Edges
Perspective Transformation
Live Scetch with Webcam
Contours
Ordered Contours and Approximation Contours
Matching Contours
Line and Circle Detection with Hough
Template Matching
Blob Detection
Corner Detection
Object Tracking with HSV Values
Face Detection, Haar Cascades

Others
Hello World

Parallel Programming
Concurrency, Multiprocessing, Parallelism
fork, pid, Zombie Process
fork()
pipe(), Unnamed Pipes
fork() and pipe()
FIFOs, Named Pipes
File Locking, Setting and Clearing a Lock
File Locking Exercise
Message Queues
Message Queues Example
Shared Memory Segments
Shared Memory Segments Example
Message Passing Interface
MPI - Send, Receive
MPI - Broadcast
MPI - Scatter, Gather

Popular Algorithms
Tower of Hanoi
Johnson and Trotter
Lexicographic Permute
Binary Reflected Gray Code
Binary Search Algorithm
Quick Select
Interpolation Search
Counting One Bits
Merge Sort Algorithm
Quick Sort Algorithm

Python
input(), print()
Lists
Tuples, Dictioneries
Conditions, if, elif, else
for loop and in keyword
for loop and range() function
List Comprehension
Functions in Python, lambda, global
Modules, math, random, time
Object Oriented, Classes
Object Oriented, Inheritance, super()
Exception Handling, try, except, finally
File Operations in Python, open()
File Operations in Python, read(), readlines()
File Operations in Python, tell(), seek()
Numerical and String Operations
Set and List Operations
SQL Connection and Data Manipulation
Advanced Functions, args, kwargs
Advanced Functions, Decorators, Nested Functions
Iterator
Generators, yield
Time Operations, datetime module
os and sys modules
Scraping Websites with BeatifulSoup
Getting IMDB Top 250 Movies with BeautifulSoup
Mail Operations with smtp
Image Manipulation, Pillow
PyQt5, Adding Button, Label and Image
PyQt5, Layouts, Adding Functions
PyQt5, QLineEdit
PyQt5, User Login
PyQt5, User Login with Database Connection
PyQt5, Usage of Checkbox
PyQt5, Usage of RadioButton
PyQt5, Creating Menu and Shortcuts
PyQt5, QTextEdit, QFileDialog, Notepad Project
PyQt5, Notepad Application with Menu
PyQt5, Designing Forms with QtDesigner
NumPy, Arrays
NumPy, Indexes, Filters
NumPy, Operators and Array Operations
Pandas, Series
Pandas, DataFrames
Pandas, MultiIndexes
Pandas, Missing Values, NaN
Pandas, Importing and Exporting Data
Pandas, Operations, groupby, join, merge
Matplotlib, Creating and Designing Graphs
Creating Executable Files
Selenium Installation, First Project, eksisozluk
Selenium, Random Pages, Entries from eksisozluk
Selenium, Instagram Auto Login
Selenium, Writing Instagram Followers to a File
Scrapy, Installation
Scrapy, Creating Spyders, quotestoscrape
Scrapy, Selectors, XPath, CSS
Scrapy, Writing Data to Json File
Scrapy, Following Links
Scrapy, kitapyurdu top100
Scrapy, sinemalar.com top1000
Scrapy, IMDB top250
map(), reduce(), filter(), zip(), enumerate()

SQL
SELECT FROM
INSERT INTO VALUES
UPDATE SET
DELETE FROM
WHERE
SELECT DISTINCT
ORDER BY
TOP, LIMIT, ROWNUP
SQL Komutları
String İşlemleri
Veri Tipleri
SUM, COUNT, MAX, MIN, AVG, GROUP BY
JOIN
Subquery

Son Yorumlar
Hello. And Bye. | Contact Management Application

Iris - Classification with Visualization

Kategori: Machine Learning, 14 Aralık 2019
Iris - Classification with Visualization

Iris veri seti üzerinde daha önceden çalışmış, gördüğümüz algoritmaları veriseti üzerinde denemiştik. Bu yazımızda yine Iris veriseti üzerinde, aynı algoritmaları test edeceğiz. Fakat bu sefer sonuçların tamamı görsel olacak. Verileri 3 boyutlu değil 2 boyutlu ... Devamını Oku

JanFranco | 3 | 0 | 4 min read

Iris - Classification

Kategori: Machine Learning, 14 Aralık 2019
Iris - Classification

Bu yazımızda machine learning, data mining prensiplerine giriş bölümünde anlatılan iris veri seti üzerinde sınıflandırma algoritmalarını test edeceğiz. Iris veri seti sklearn kütüphanesinde hazır olarak bulunmaktadır. Kütüphaneleri ve veri setini import edelim:

 from ...
		    
Devamını Oku

JanFranco | 3 | 0 | 12 min read

Visualization - Comparison of Classifiers

Kategori: Machine Learning, 13 Aralık 2019
Visualization - Comparison of Classifiers

Bu yazımızda şu ana kadar gördüğümüz sınıflandırma algoritmalarını, özel olarak hazırlanmış 3 veri seti üzerinde test edip, nasıl bir sınıflandırma yaptıklarını 2 boyutlu olarak görselleştireceğiz. Kütüphaneleri import edelim:

 import numpy as np import ...
		    
Devamını Oku

JanFranco | 5 | 0 | 4 min read

Visualization - 3D Visualization

Kategori: Machine Learning, 12 Aralık 2019
Visualization - 3D Visualization

sklearn kütüphanesinde bulunan hazır veri setlerinden iris veri setini import edip, verileri 2 boyutlu ve 3 boyutlu olarak görselleştireceğiz. Kütüphaneleri ve veri kümesini import edelim:

 from sklearn import datasets import matplotlib.pyplot as plt ...
		    
Devamını Oku

JanFranco | 5 | 0 | 13 min read

Random Forest Classifier

Kategori: Machine Learning, 09 Aralık 2019
Random Forest Classifier

Random forest algoritmasını görmüştük. Regression bölümünde kullanmıştık. Classify problemlerinde de kullanabiliriz:

 import pandas as pd from sklearn.impute import SimpleImputer from sklearn.metrics import confusion_matrix from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split from sklearn.preprocessing ...
		    
Devamını Oku

JanFranco | 9 | 0 | 5 min read

Decision Tree Classifier

Kategori: Machine Learning, 09 Aralık 2019
Decision Tree Classifier

Karar ağaçı algoritmasını Regression'da anlatmıştım. Bu yazıda aynı algoritmayı sınıflandırma için kullanacağız. Önceki bilgilere ek olarak entropi ve gini kavramlarından bahsedeceğim. Karar ağaçlarının yapısını biliyoruz fakat ilk node, ilk element nasıl seçiliyor? Veri kümemizi hatırlarsak ... Devamını Oku

JanFranco | 7 | 0 | 5 min read

Naive Bayes

Kategori: Machine Learning, 06 Aralık 2019
Naive Bayes

Naive bayes algoritması, karmaşık veri kümelerini basit bir olasılık hesabı yaparak çözümlemeye çalışır. Koşullu olasılık tekniğini kullanır. Formül aşağıda verilmiştir:

 P(x|c).P(c) P(c|x) = -------------- P(x) 
Kütünhaleri ve veri kümesini alalım. Daha önce ... Devamını Oku

JanFranco | 8 | 0 | 2 min read

Support Vector Machine

Kategori: Machine Learning, 06 Aralık 2019
Support Vector Machine

Support Vector Machine algoritmasını daha önce görmüştük. Amaç maximum margin değerini bularak bir doğru çizmekti. Classification problemlerinde de kullanacağımızdan bahsetmiştim. Daha önce açıkladığımız için direk koda geçelim:

 import pandas as pd from sklearn.svm ...
		    
Devamını Oku

JanFranco | 7 | 0 | 5 min read

K Neirest Neighborhood

Kategori: Machine Learning, 06 Aralık 2019
K Neirest Neighborhood

Sınıflandırma algoritmalarından K-NN yani K-Nearest Neighbours algoritması ile devam ediyoruz. Algoritmayı anlamak için iki boyutlu bir düzlem düşünelim. İki sınıf ikiye ayrılmış durumda olsun. Yeni bir veri geldiğinde, o verinin düzlemde olduğunu noktaya en yakın ... Devamını Oku

JanFranco | 8 | 0 | 5 min read

Logistic Regression

Kategori: Machine Learning, 04 Aralık 2019
Logistic Regression

Logistic Regression ile birlikte sınıflandırma yani classification algoritmalarına giriyoruz. Önceki yazılarımızda Regression algoritmalarını görmüştük. Bu algoritmanın ismi Logistic Regression olmasına rağmen genellikle classification problemlerinde kullanılıyor.

Sınıflandırma problemlerine girmişken, sınıflandırma ile regresyon arasındaki farkı da ... Devamını Oku

JanFranco | 7 | 0 | 5 min read