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Uncategorized

Game Control Using OpenCV and Numpy Python

Download Free Source Code of a gaming control using python, OpenCV and Numpy with Complete Tutorial. Use the Python openCV and Numpy libraries to monitor a steering wheel racing game. It offers you the feeling of futuristic driving.
The panel is split in 4 sections, logically. When a certain color (in my case Blue) is observed in certain pieces it is considered a main click. Suppose Blue color has been identified at the top left of the panel, so a “A” key press is begun and the car turns left. The color boundaries were established using color.py, in which we defined Blue color range of HSV values. Directkeys.py file using key press and unlock function.
To manage my project I use a MacOS and a Spyder. This application is compatible on every MacOS app. If you are using Windows OS then the directkeys.py file could have been changed.

Download Source Code

Categories
PHP Courses Uncategorized

PHP for Beginners: How to Build an E-Commerce Store

What you’ll learn

  • At the end you will be able to build any E-commerce application with PHP
  • At the end of this course you will be able to upload your application online

Requirements

  • All Students Should know the following
  • HTML
  • VARIABLES
  • ARRAYS
  • FUNCTIONS
  • LOOPS
  • POST and GET REQUEST
  • MYSQL

Hands on Real Life Project inside!

On Demand E-commerce Skills Inside

After creating a very successful PHP for beginners course, I’m back with another Amazing course that will take your basic PHP skills to another level.

This course comes packed with new tricks and code format that would take your basic PHP skills to different heights.

On this course you will learn how to make a complete e-commerce store that will communicate with Paypal to send requests for processing and will also receive data back to the admin for sale reporting.

If you have taken my other PHP courses, you will notice that this course’s project is more function based, more secured, we have more techniques, more organized and we upload our final application to the web.

MORE MONEY ……

Completing this course will prepare you to build E-commerce stores online for clients that would gladly pay really good for your work.

My first PHP course prepares you with all the knowledge but this course will polish all that knowledge and at the same time show you new tricks and grow your skills.

Who this course is for:

  • Students Who Want to build E-commerce Systems or Websites should take this course

Take Course

Categories
Android Courses Firebase Uncategorized

Professional iOS Chat App with Social Login using Firebase 3

What you’ll learn
  • FREE preview first HALF of the course including social login with Firebase 3 and complete front-end in Swift.
  • Build professional iOS chat apps which can be published on the app store right away to serve millions of users.
  • Best coding practices and intuitive, high-level thinking to become a great iOS developer
  • Master Firebase 3 for realtime iOS apps.
  • Design attractive UI for iOS apps.
  • Use Firebase to Implement a complete authentication system supporting social login such as Google Sign-In.
  • Master Firebase storage and synchronization features to store and synchronize media data for realtime applications.
Requirements
  • You need a Mac, with XCode 7 installed (which is free).
  • You should know Swift 2.3 basic.

Description

Half of this awesome course is FREE

We are happy to offer a half of the course for FREE. We strongly recommend you to go through the free lectures before deciding to join us. 😀

This course is about becoming professional

This course teaches you to build a complete messaging app at an industry-standard level, which can be published on the app store right away to serve millions of people. The course spirit is to equips you with good coding practices and intuitive, high-level thinking, which are crucial in becoming a professional developer.

You will build the must-have feature backed by the must-learn framework

In this course, you’ll learn to build a pretty, full-function messaging app which lets users sign in with their social network accounts, and send text, photo, and video messages. During the course, you’ll learn how to use Firebase to handle real-time data and synchronize media data such as photos and videos. The course also helps you to easily integrate chat functionality into your own apps, which is a must in publishing an app these days.

You know the what and why of every single line of code

The course equips you with good coding practices and intuitive, high-level thinking, which are crucial in becoming a decent developer. Each module or lecture starts with a clear roadmap to help you see the big picture and how each element fits in. Every step or line of code is well-motivated and followed by intuitive explanations. At any time during the course, you will be able to fully aware of what you are doing and why you are doing that.

You will master the hottest backend service and messaging library in the hottest programming language

In this course, we’ll teach you to build a full-function iOS messaging app using the JSQMessagesViewController library. The app will be written in Swift programming language with the new Firebase backend. We focus on helping you to write clean and extensible code so that you can build your own chat apps with various database and backend services, or integrate the chat functionality into your own apps.

JSQMessagesViewController is a open-source iOS messaging library that becomes increasingly popular recently. It offers ready-to-use messaging features which can be easily integrated into your apps. You’ll learn to use JSQMessagesViewController to build complete chat apps that allow users to send media messages such as photos and videos with thumbnails.

Firebase is a mobile-backend-as-a-service that provides several features for building powerful mobile apps. Firebase has three core services: a realtime database, user authentication and hosting. With the Firebase iOS SDK, you can use these services to build powerful apps without writing a single line of server code.

Firebase offers unlimited possibilities to sync your apps data to the cloudfor storing and protection. When a Firebase database updates, all connected users receive updates in realtime automatically. With Firebase, power is in your hands – without learning other languages or frameworks.

Who this course is for:
  • Who know a bit of iOS programming but still don’t know how to build a complete, viable iOS app.
  • Anyone who wants to learn IOS programming
  • Anyone who wants to turn ideas into professional apps that can serve millions of users.

Take Course

Categories
Data Science Data Sciences Books Machine Learning Machine Learning, AI & Deep Learning Uncategorized

Complete Machine Learning and Data Science: Zero to Mastery

What you’ll learn
  • Become a Data Scientist and get hired
  • Master Machine Learning and use it on the job
  • Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
  • Use modern tools that big tech companies like Google, Apple, Amazon and Facebook use
  • Present Data Science projects to management and stakeholders
  • Learn which Machine Learning model to choose for each type of problem
  • Real-life case studies and projects to understand how things are done in the real world
  • Learn best practices when it comes to Data Science Workflow
  • Implement Machine Learning algorithms
  • Learn how to program in Python using the latest Python 3
  • How to improve your Machine Learning Models
  • Learn to pre-process data, clean data, and analyze large data.
  • Build a portfolio of work to have on your resume
  • Developer Environment setup for Data Science and Machine Learning
  • Supervised and Unsupervised Learning
  • Machine Learning on Time Series data
  • Explore large datasets using data visualization tools like Matplotlib and Seaborn
  • Explore large datasets and wrangle data using Pandas
  • Learn NumPy and how it is used in Machine Learning
  • A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
  • Learn to use the popular library Scikit-learn in your projects
  • Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
  • Learn to perform Classification and Regression modelling
  • Learn how to apply Transfer Learning
Requirements
  • No prior experience is needed (not even Math and Statistics). We start from the very basics.
  • A computer (Linux/Windows/Mac) with internet connection.
  • Two paths for those that know programming and those that don’t.
  • All tools used in this course are free for you to use.
Description

Become a complete Data Scientist and Machine Learning engineer! Join a live online community of 200,000+ engineers and a course taught by industry experts that have actually worked for large companies in places like Silicon Valley and Toronto. This is a brand new Machine Learning and Data Science course just launched January 2020! Graduates of Andrei’s courses are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, + other top tech companies.

Learn Data Science and Machine Learning from scratch, get hired, and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).

This comprehensive and project based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real world projects to add to your portfolio. You will get access to all the code, workbooks and templates (Jupyter Notebooks) on Github, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on the job skills that employers want.

The curriculum is going to be very hands on as we walk you from start to finish of becoming a professional Machine Learning and Data Science engineer. The course covers 2 tracks. If you already know programming, you can dive right in and skip the section where we teach you Python from scratch. If you are completely new, we take you from the very beginning and actually teach you Python and how to use it in the real world for our projects. Don’t worry, once we go through the basics like Machine Learning 101 and Python, we then get going into advanced topics like Neural Networks, Deep Learning and Transfer Learning so you can get real life practice and be ready for the real world (We show you fully fledged Data Science and Machine Learning projects and give you programming Resources and Cheatsheets)!

The topics covered in this course are:

– Data Exploration and Visualizations

– Neural Networks and Deep Learning

– Model Evaluation and Analysis

– Python 3

– Tensorflow 2.0

– Numpy

– Scikit-Learn

– Data Science and Machine Learning Projects and Workflows

– Data Visualization in Python with MatPlotLib and Seaborn

– Transfer Learning

– Image recognition and classification

– Train/Test and cross validation

– Supervised Learning: Classification, Regression and Time Series

– Decision Trees and Random Forests

– Ensemble Learning

– Hyperparameter Tuning

– Using Pandas Data Frames to solve complex tasks

– Use Pandas to handle CSV Files

– Deep Learning / Neural Networks with TensorFlow 2.0 and Keras

– Using Kaggle and entering Machine Learning competitions

– How to present your findings and impress your boss

– How to clean and prepare your data for analysis

– K Nearest Neighbours

– Support Vector Machines

– Regression analysis (Linear Regression/Polynomial Regression)

– How Hadoop, Apache Spark, Kafka, and Apache Flink are used

– Setting up your environment with Conda, MiniConda, and Jupyter Notebooks

– Using GPUs with Google Colab

By the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects like Heart Disease Detection, Bulldozer Price Predictor, Dog Breed Image Classifier, and many more. By the end, you will have a stack of projects you have built that you can show off to others.

Here’s the truth: Most courses teach you Data Science and do just that. They show you how to get started. But the thing is, you don’t know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don’t really explain things well enough for you to go off on your own and solve real life machine learning problems.

Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial. No! This course will push you and challenge you to go from an absolute beginner with no Data Science experience, to someone that can go off, forget about Daniel and Andrei, and build their own Data Science and Machine learning workflows.

Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.

You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean!

Click “Enroll Now” and join others in our community to get a leg up in the industry, and learn Data Scientist and Machine Learning. We guarantee this is better than any bootcamp or online course out there on the topic. See you inside the course!

Taught By:

Andrei Neagoie is the instructor of the highest rated Development courses on Udemy as well as one of the fastest growing. His graduates have moved on to work for some of the biggest tech companies around the world like Apple, Google, Amazon, JP Morgan, IBM, UNIQLO etc… He has been working as a senior software developer in Silicon Valley and Toronto for many years, and is now taking all that he has learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer allows in life.

Having been a self taught programmer, he understands that there is an overwhelming number of online courses, tutorials and books that are overly verbose and inadequate at teaching proper skills. Most people feel paralyzed and don’t know where to start when learning a complex subject matter, or even worse, most people don’t have $20,000 to spend on a coding bootcamp. Programming skills should be affordable and open to all. An education material should teach real life skills that are current and they should not waste a student’s valuable time.   Having learned important lessons from working for Fortune 500 companies, tech startups, to even founding his own business, he is now dedicating 100% of his time to teaching others valuable software development skills in order to take control of their life and work in an exciting industry with infinite possibilities.

Andrei promises you that there are no other courses out there as comprehensive and as well explained. He believes that in order to learn anything of value, you need to start with the foundation and develop the roots of the tree. Only from there will you be able to learn concepts and specific skills(leaves) that connect to the foundation. Learning becomes exponential when structured in this way.

Taking his experience in educational psychology and coding, Andrei’s courses will take you on an understanding of complex subjects that you never thought would be possible.

See you inside the course!

Who this course is for:
  • Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science, Python
  • You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable
  • Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field
  • You’re looking for one single course to teach you about Machine Learning and Data Science and get you caught up to speed with the industry
  • You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it”
  • You want to learn to use Deep Learning and Neural Networks with your projects
  • You want to add value to your own business or company you work for, by using powerful Machine Learning tools.

Categories
Data Science Data Sciences Books Machine Learning, AI & Deep Learning Uncategorized

Data Science & Machine Learning : Hands on Data Science 2020

What you’ll learn
  • You will Learn one of the most in-demand skill of 21st-century Data Science
  • Add Data science skills : python, numpy, pandas, Plotly, tableau, machine learning, statistics, probability in your resume
  • Apply linear regression and logistics regression on real dataset.
  • Crash course on python
  • Apply matrix operation with Numpy – Numerical python library
  • Visualize your data with mother of all visualization library available in Python : MatplotLIb
  • Perform Data analysis, wrangling and cleaning with pandas library
  • Get hands on with interactive visualization library Plotly
  • Getting start with data visualization tool, Tableau
  • Data Pre-processing technique – Missing data, Normalization, one hot encoding,
  • Importing data in Python from different sources, Files
  • Web Scraping to download web page and extract data
  • Data scaling and transformation
  • Exploratory Data analysis
  • Feature engineering process in Machine Learning system design
  • Machine learning theory
  • Apache spark installation : pyspark
  • Getting started with spark session
  • Mathey required for machine learning : Statistics, probability
  • Setup Data Science Virtual machine on Microsoft Azure Cloud
Requirements
  • Basic of Python programming
  • High school mathematics
Description

Welcome to Complete Ultimate course guide on Data Science and Machine learning with Python.

Have you ever thought about

How amazon gives you product recommendation,

How Netflix and YouTube decides which movie or video you should watch next,

Google translate translate one language to another,

How Google knows what is there in your photo,

How  Android speech Recognition or Apple siri understand your speech signal with such high accuracy.

If you would like algorithm or technology running behind that,  This is first course to get started in this direction.

==============================================

This course has more than 100 – 5 star rating.

What previous students have said: 

“This is a truly great course! It covers far more than it’s written in its name: many data science libraries, frameworks, techniques, tips, starting from basics to advanced level topics. Thanks a lot!  ”

This course has taught me many things I wanted to know about pandas. It covers everything since the installation steps, so it is very good for anyone willing to learn about data analysis in python /jupyter environment.”

“learning valuable concepts and feeling great.Thanks for this course.”

Good explanation, I have laready used two online tutorials on data -science and this one is more step by step, but it is good”

“i have studied python from other sources as well but here i found it more basic and easy to grab especially for the beginners. I can say its best course till now . it can be improved by including some more examples and real life data but overall i would suggest every beginner to have this course.”

“The instructor is so good, he helps you in all doubts within an average replying time of one hour. The content of the course and the way he delivers is great.”

==================================================

Why Data Science Now?

Data Scientist: The Sexiest Job of the 21st Century – By Harvard Business review

There is huge sortage of data scientist currently software industry is facing.

The average data scientist today earns $130,000 a year  by  glassdoor.

Want to join me for your journey towards becoming Data Scientist, Machine Learning Engineer.

This course has more than 100+ HD –  quality video lectures and is over 13+ hours in content.

This is first introductory course to get started data analysis, Machine learning and towards  AI algorithm implementation

This course will teach you – All Basic python library required for data analysis process.

  • Python  crash course
  • Numerical Python – Numpy
  • Pandas – data analysis
  • Matplotlib for data visualization
  • Plotly and Business intelligence tool Tableau
  • Importing Data in Python from different sources like .csv, .tsv, .json, .html, web rest Facebook API
  • Data Pre-Processing like normalization, train test split, Handling missing data
  • Web Scraping with python BeautifulSoup – extract  value from structured HTML Data
  • Exploratory data analysis on pima Indian diabetes dataset
  • Visualization of Pima Indian diabetes dataset
  • Data transformation and Scaling Data –  Rescale Data, Standardize Data, Binarize Data, normalise data
  • Basic introduction to What is Machine Learning, and  Scikit learn overview Its type, and comparison with traditional system. Supervised learning vs Unsupervised Learning
  • Understanding of regression, classification and clustering
  • Feature selection and feature elimination technique.
  • And Many Machine learning algorithm yet to come.
  • Data Science Prerequisite : Basics of Probability and statistics
  • Setup Data Science and Machine learning lab in Microsoft Azure Cloud

This course is for beginner and some experienced programmer who want to make career in Data Science and  Machine learning, AI.

Prerequisite:

  • basic knowledge in python programming (will be covered in python)
  • High School mathematics

Enroll in this course, take look at brief curriculum of this course and take first step in the wonderful world of Data.

See you in field.

Sincerely,

Ankit Mistry

Who this course is for:
  • Anyone who is interested in Data Science
  • Anyone who wants to learn – How to analyze data
  • Those who want to make a career in Data Analytics, Machine Learning, Data Science

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Categories
Machine Learning, AI & Deep Learning Uncategorized

Machine Learning Made Easy : Beginner to Advanced using R

What you’ll learn
  • R Programming, Data Handling and Cleaning, Basic Statistics, Classical Machine Learning Algorithms, Model Selection and Validation, Advanced Machine Learning Algorithms, Ensemble Learning.
  • Write your own R scripts and work in R environment.
  • Import, manipulate, clean up, sanitize and export datasets.
  • Understand basic statistics and implement using R.
  • Understand data science life cycle while understanding steps of building, validating, improving and implementing the machine learning models.
  • Do powerful analysis on data, find insights and present them in visual manner.
  • Learn classical algorithms like Linear Regression, Logistic Regression, Decision Trees and advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means.
  • Know how each machine learning algorithm works and which one to choose according to the type of problem.
  • Build more than one powerful machine learning model and be able to select the best one and improve it further.
Requirements
  • Familiarity with high school mathematics.
Description

Want to know how Machine Learning algorithms work and how people apply it to solve data science problems? You are looking at right course!

This course has been created, designed and assembled by professional Data Scientists who have worked in this field for nearly a decade. We can help you understand the complex machine learning algorithms while keeping you grounded to the implementation on real business and data science problems.

We will let you feel the water and coach you to become a full swimmer in the realm of data science and Machine Learning. Every tutorial will increase your skill level by challenging your ability to foresee, yet letting you improve upon self.

We are sure that you will have fun while learning from our tried and tested structure of course to keep you interested in what’s coming next.

Here is how the course is going to work:

  • Part 1 – Introduction to R Programming.
    • This is the part where you will learn basic of R programming and familiarize yourself with R environment.
    • Be able to import, export, explore, clean and prepare the data for advance modelling.
    • Understand the underlying statistics of data and how to report/document the insights.
  • Part 2 – Machine Learning using R
    • Learn, upgrade and become expert on classic machine learning algorithms like Linear Regression, Logistic Regression and Decision Trees.
    • Learn which algorithm to choose for specific problem, build multiple model, learn how to choose the best model and be able to improve upon it.
    • Move on to advance machine learning algorithms like SVM, Artificial Neural Networks, Reinforced Learning, Random Forests and Boosting and clustering algorithms like K-means.

Features:

  • Fully packed with LAB Sessions. One to learn from and one for you to do it yourself.
  • Course includes R code, Datasets and other supporting material at the beginning of each section for you to download and use on your own.
  • Quiz after each section to test your learning.

Bonus:

  • This course is packed with 5 projects on real data related to different domains to prepare you for wide variety of business problems.
  • These projects will serve as your step by step guide to solve different business and data science problems.
Who this course is for:
  • Anyone interested in Data Science and Machine Learning.
  • Students who want a head start in Data Science field.
  • Data analysts who want to upgrade their skills in Machine Learning.
  • People who want to add value to their work and business by using Machine Learning.
  • People with basics understanding of classical machine learning algorithms like linear regression or logistic regression, but want to learn more about it.
  • People interested in understanding the application of machine learning algorithms on real business problems.
  • People interested in understanding how a machine learning algorithm works and what’s the math behind it.

Take Course