computer vision projects for beginnners

Computer vision projects for beginners:

Python-Learning

1. Photo Sketching

                       

2. Contours Detection

3. Edge Detection

4. Color Detection

5. Face Hide/Blur

6. Human/Animal Counting

7. Object/Face Detection

8. Object Tracking

9. Thief Alarm in Yard

10. Image Search Engine

top 10 free E-books to learn data science

Top 10 free E-books to learn Data Science:

E-books are known as Electronic Book.This is the medium of recording information.

You can download E-books by contacting us

• Neural Networks and deep learning

• Think Bayes

• Statistical Learning with Sparsity:The Lasso and Generalizations

• The Field Guide of Data Science

• The White Book of data science

• Machine Learning

• Beginners Guide to Analytics

• Data Science:Theories, Models,Algorithms,and Analytics

• Automating Boring Stuff with Python

• An introduction to statistical Learning

R vs Python

R vs Python:

Which One is better for data science?

R Programming:

R is one of the oldest programming language developed by academics and statisticians.R comes into existence in year 1995. Now R is providing the richest ecosystem for data analysis.

Python Programming:

On the other hand Python can do the same tasks as R programming language does. The major features of python are data wrangling, engineering, web scraping and also very useful for hackers and so on.

Difference R or Python:

• R is more functional, Python is more object-oriented.
• R has more data analysis built-in, Python relies on packages.
• R has more statistical support in general.
• Straightforward to do non-statistical tasks in Python.
• Parallels between the data analysis workflow in both.
• R is more functional, it provides variety of functions the data scientist i.e Im, predict and son on. Most of the work done by functions in R.
• R was created as a statistical language, and it shows, statsmodels in python and other packages provide decent coverage for statistical methods, but the R ecosystem is far from large.
• R provides the build in data analysis for summary statistics, it is supported by summary built-in functions in R.
• Well placed libraries like beautifulsoup and request.
• Web scrapping in python is much easier than R.This applies to other tasks that we don't see closely.

Types of python algorithm

Types Of Algorithms You Should Know:

(PYTHON BASED)

 

If you want to learn any type of programming language then you should know about the algorithms. Any type of programming language is based on algorithms. Algorithms are the type of sequence in computer language that tells us how to implement the program.

In python their are many types of algorithms here we discuss below:

1. Search Algorithm:

Design to retrieve information stored within a data structure.

Examples:

• Linear Search
• Binary Search
• Depth First Search
• Breadth First Seach

2. Sort Algorithms:

This is used to rearrange arrays or as we says that if we have some disorder type of elements in an array we can make that arrange by using sort algorithm.

Examples:

• Quick Sort
• Insertion Sort
• Selection Sort
• Bubble Sort
• Merge Sort
• Radix Sort
• Heap Sort

3. Greedy Algorithms:

An algorithm paradigm that builds up a solution piece by piece, and always choosing the next piece, suppose we have 2 or more elements and we want to show them one by one and that offers the most obvious and immediate benefits.

Examples:

• Huffman Coding
• Fractional Knapsack
• Problem
• Activity Selection
• Job Sequencing Problem

4. Recursive Algorithms:

An algorithm which calls itself with smaller or simpler input values. It returned the result of chain that you input until it hits the original problem.

Examples:

• Fractional
• Exponential
•  Tower of Hanoi
• Tree Traversal
• Depth First Search

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