Simpliv

Course Description:

Basic Course Description

MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language which is frequenlty being used by engineering and science students. While teaching to students and observing different MATLAB related courses on Simpliv for more than six months now. I realized that there is a need for a course which should cover the key data types such as Cells, tables, time tables, structures and Map containers which should provide the students with the essential skills for taking full advantage of MATLAB strengths in data analysis and programming.

In this course we not only cover these data Types but also demonstrates different functions and operation and their conversions to make analysis and programming a greater experience.

The following are the outlines of this course.

Segment 1: introduction to the Course
Segment 2: Cell Data Type
Segment 3: Table Data Type
Segment 4: Time Table Data Type
Segment 5: Structures
Segment 6: Map Containers
Segment 7: Conversion between Different Data Types
Your Benefits and Advantages

You receive knowledge from a Ph.D. in Computer science with over 10 years of teaching and 15 years of programming experience and another decade of experience in using MATLAB
The instructor has 6 courses on simpliv on MATLAB including a best seller course
The overall rating in these courses are (4.5/5)
If you do not find the course useful, you are covered with 30 day money back guarantee, full refund, no questions asked!
You have lifetime access to the course
You have instant and free access to any updates i add to the course
You have access to all Questions and discussions initiated by other students
You will receive my support regarding any issues related to the course
Check out the curriculum and Freely available lectures for a quick insight
Student Testimonials!

This is the second Simpliv class on Matlab I've taken. Already, a couple important concepts have been discussed that weren't discussed in the previous course. I'm glad the instructor is comparing Matlab to Excel, which is the tool I've been using and have been frustrated with. This course is a little more advanced than the previous course I took. As an engineer, I'm delighted it covers complex numbers, derivatives, and integrals. I'm also glad it covers the GUI creation. None of those topics were covered in the more basic introduction I first took.

Jeff Philips

Great information and not talking too much, basically he is very concise and so you cover a good amount of content quickly and without getting fed up!

Oamar Kanji

The course is amazing and covers so much. I love the updates. Course delivers more then advertised. Thank you!

Josh Nicassio

Student Testimonials! who are also instructors in the MATLAB category

"Concepts are explained very well, Keep it up Sir...!!!"

Engr Muhammad Absar Ul Haq instructor of course "Matlab keystone skills for Mathematics (Matrices & Arrays)"

It's time to take Action!

Click the "Add to Cart" button at the top right now!

Time is limited and Every second of every day is valuable.

I am excited to see you in the course!

Best Regrads,

Dr. Nouman Azam

Who is the target audience?

Researchers, Entrepreneurs, Instructors, College Students, Engineers, Programmers, Simulators
Basic knowledge
General know how of MATLAB programming
What you will learn
The essential and unique MATLAB data types necessary for MATLAB programming and data analysis
At the end you can confidently use different data types and structures such as Cells, Tables, Time Tables, Structures and Map Containers
You will be able to convert between different data types

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/developmenttool/advance-matlab-data-types-and-data-structures
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Machine Learning

Course Description:

This course will teach you how to maximize your potential using the Unity editor. By using the techniques taught in this course, you will speed up your development time and customize your Unity workflow. You will learn how to make Unity user friendly to your preferences, techniques, and workflows.

First, we will look at some built-in options Unity gives developers for customizing the editor. We will learn how to customize window layout, console output, and more. Next, we will look at how to use editor scripting to our advantage. Unity allows us to customize and extend the functionality of the editor by writing C# code. The final topic we will look at is customizing the inspector. This will give us the ability to edit and modify our game objects in the scene.

By the end of this course you will have a well-rounded knowledge of how to customize each of these areas of Unity. The result will be a more efficient and effective development process allowing you to get more quality work done in less time.

This course also comes with a PDF review sheet that you can print out covering all of the major terms and functions taught in this course and screenshot examples of using each in Unity.

Who is the target audience?

Anyone who wants to take their Unity C# skills up a level
Developers who are interested in making tools for the Unity Asset Store but don't know where to start
Students who want to obtain a game industry job as a Unity Developer
Basic knowledge
Some basic Unity experience in C#
What you will learn
Learn how to make tools in Unity
Take full advantage of the power of Unity
Speed up your development process
Understand how asset store tools are created
Get knowledge of industry-standard techniques

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/developmenttool/beginners-guide-to-editor-scripting-in-unity
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Game Design

Course Description:

This course is a really comprehensive guide to the Google Cloud Platform - it has 25 hours of content and 60 demos.

The Google Cloud Platform is not currently the most popular cloud offering out there - that's AWS of course - but it is possibly the best cloud offering for high-end machine learning applications. That's because TensorFlow, the super-popular deep learning technology is also from Google.

What's Included:

Compute and Storage - AppEngine, Container Enginer (aka Kubernetes) and Compute Engine
Big Data and Managed Hadoop - Dataproc, Dataflow, BigTable, BigQuery, Pub/Sub
TensorFlow on the Cloud - what neural networks and deep learning really are, how neurons work and how neural networks are trained.
DevOps stuff - StackDriver logging, monitoring, cloud deployment manager
Security - Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accounts
Networking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect
Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)
Who is the target audience?

Yep! Anyone looking to use the Google Cloud Platform in their organizations
Yep! Any one who is interesting in architecting compute, networking, loading balancing and other solutions using the GCP
Yep! Any one who wants to deploy serverless analytics and big data solutions on the Google Cloud
Yep! Anyone looking to build TensorFlow models and deploy them on the cloud
Basic knowledge
Basic understanding of technology - superficial exposure to Hadoop is enough.
What you will learn
Deploy Managed Hadoop apps on the Google Cloud
Build deep learning models on the cloud using TensorFlow
Make informed decisions about Containers, VMs and AppEngine
Use big data technologies such as BigTable, Dataflow, Apache Beam and Pub/Sub

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/hadoop/gcp-complete-google-data-engineer-and-cloud-architect-guide
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Hadoop

Course Description:

If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We’re approaching a new era where only apps and games that are considered “smart” will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.

In this course, you will:

Master the 3 fundamental branches of applied Machine Learning: Image & Video Processing, Text Analysis, and Speech & Language Recognition
Develop an intuitive sense for using Machine Learning in your iOS apps
Create 7 projects from scratch in practical code-along tutorials
Find pre-trained ML models and make them ready to use in your iOS apps
Create your own custom models
Add Image Recognition capability to your apps
Integrate Live Video Camera Stream Object Recognition to your apps
Add Siri Voice speaking feature to your apps
Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit.
Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder–even if you have zero experience
Get FREE unlimited hosting for one year
And more!
This course is also full of practical use cases and real-world challenges that allow you to practice what you’re learning. Are you tired of courses based on boring, over-used examples? Yes? Well then, you’re in a treat. We’ll tackle 5 real-world projects in this course so you can master topics such as image recognition, object recognition, and modifying existing trained ML models. You’ll also create an app that classifies flowers and another fun project inspired by Silicon Valley™ Jian Yang’s masterpiece: a Not-Hot Dog classifier app!

Why Machine Learning on iOS

One of the hottest growing fields in technology today, Machine Learning is an excellent skill to boost your your career prospects and expand your professional tool kit. Many of Silicon Valley’s hottest companies are working to make Machine Learning an essential part of our daily lives. Self-driving cars are just around the corner with millions of miles of successful training. IBM’s Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google DeepMind’s computer, can beat the world master of the game Go, a game where it was thought only human intuition could excel.

In 2017, Apple has made Machine Learning available in iOS 11 so that anyone can build smart apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games that do not have an ML layer will not be appealing to users. Whether you wish to change careers or create a second stream of income, Machine Learning is a highly lucrative skill that can give you an amazing sense of gratification when you can apply it to your mobile apps and games.

Why This Course Is Different

Machine Learning is very broad and complex; to navigate this maze, you need a clear and global vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In this course, each section focuses on distinct use cases and real projects so that your learning experience is best structured for mastery.

This course brings my teaching experience and technical know-how to you. I’ve taught programming for over 10 years, and I’m also a veteran iOS developer with hands-on experience making top-ranked apps. For each project, we will write up the code line by line to create it from scratch. This way you can follow along and understand exactly what each line means and how to code comes together. Once you go through the hands-on coding exercises, you will see for yourself how much of a game-changing experience this course is.

As an educator, I also want you to succeed. I’ve put together a team of professionals to help you master the material. Whenever you ask a question, you will get a response from my team within 48 hours. No matter how complex your question, we will be there–because we feel a personal responsibility in being fully committed to our students.

By the end of the course, you will confidently understand the tools and techniques of Machine Learning for iOS on an instinctive level.

Don’t be the one to get left behind. Get started today and join millions of people taking part in the Machine Learning revolution.

topics: ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection

Who is the target audience?

People with a basic foundation in iOS programming who would like to discover Machine Learning, a branch of Artificial Intelligence
People who want to pursue a career combining app development and Machine Learning to become a hybrid iOS developer and ML expert
Developers who would like to apply their Machine Learning skills by creating practical mobile apps
Entrepreneurs who want to leverage the exponential technology of Machine Learning to create added value to their business could also take this course. However, this course does assume that you are familiar with basic programming concepts such as object oriented programming, variables, methods, classes, and conditional statements
Basic knowledge
Basic understanding of programming
Have access to a MAC computer or MACinCloud website
What you will learn
Build smart iOS 11 & Swift 4 apps using Machine Learning
Use trained ML models in your apps
Convert ML models to iOS ready models
Create your own ML models
Apply Object Prediction on pictures, videos, speech and text
Discover when and how to apply a smart sense to your apps

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/machinelearning/complete-ios-11-machine-learning-masterclass
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Machine Learning

Course Description:

MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language which is frequently being used by engineering and science students. In this course, we will start learning MATLAB from a beginner level, and will gradually move into more technical and advance topics. This course is designed to be general in scope which means that it will be beneficial to students in any major. Once, passed a certain learning thresholds, you will definitely enjoy MATLAB Programming. The key benefit of MATLAB is that it makes the programming available to everyone and is very fast to turn ideas into working products compared to some of the conventional programming languages such as Java, C, C++, visual basic and others.

Below is the detailed outline of this course.

Segment 1: Instructor and Course Introduction
Segment 2: Handling variables and Creating Scripts
Segment 3: Doing Basic Maths in MATLAB
Segment 4: Operations on Matrices
Segment 5: Advance Math Functions with Symbolic Data Type
Segment 6: Interacting with MATLAB and Graphics
Segment 7: Importing Data into MATLAB
Segment 8: File Handling and Text Processing
Segment 9: MATLAB Programming
Segment 10: Sharing Your MATLAB Results
Segment 11: Cell Data Type
Segment 12: Tables and Time Tables
Segment 13: Working with Structures and Map Container Data Type
Segment 14: Converting between Different Data Types
Your Benefits and Advantages:

If you do not find the course useful, you are covered with 30 day money back guarantee, full refund, no questions asked!
You will be sure of receiving quality contents since the instructors has already four courses in the MATLAB niche which are ranked in the top 10 courses in the MATLAB niche
You have lifetime access to the course
You have instant and free access to any updates i add to the course
You have access to all Questions and discussions initiated by other students
You will receive my support regarding any issues related to the course
Check out the curriculum and Freely available lectures for a quick insight
It's time to take Action!

Click the "Add to Cart" button at the top right now!

Time is limited and Every second of every day is valuable.

We are excited to see you in the course!

Best Regrads,

Dr. Nouman Azam

More Benefits and Advantages:

You receive knowledge from an experienced instructor (Dr. Nouman Azam) who is the creator of five courses on Simpliv in the MATLAB niche.
The titles of these courses are
MATLAB from A to Z: From Programming to App Desiging
Data Analysis with MATLAB for EXCEL Users.
MATLAB App Desigining: The Ultimate Guide for MATLAB Apps
Create Apps in MATLAB with App Designer (Codes Included)
Advance MATLAB Data Types and Data Structures
You find majority of these courses on the first page in the MATLAB niche
Student Testimonials for Dr. Nouman Azam!

This is the second Simpliv class on Matlab I've taken. Already, a couple important concepts have been discussed that weren't discussed in the previous course. I'm glad the instructor is comparing Matlab to Excel, which is the tool I've been using and have been frustrated with. This course is a little more advanced than the previous course I took. As an engineer, I'm delighted it covers complex numbers, derivatives, and integrals. I'm also glad it covers the GUI creation. None of those topics were covered in the more basic introduction I first took.

Jeff Philips

Great information and not talking too much, basically he is very concise and so you cover a good amount of content quickly and without getting fed up!

Oamar Kanji

The course is amazing and covers so much. I love the updates. Course delivers more then advertised. Thank you!

Josh Nicassio

Student Testimonials! who are also instructors in the MATLAB category

"Concepts are explained very well, Keep it up Sir...!!!"

Engr Muhammad Absar Ul Haq instructor of course "Matlab keystone skills for Mathematics (Matrices & Arrays)"

Who is the target audience?

Researchers, Entrepreneurs, Instructors, College Students, Engineers, Programmers, Simulators who wants to quickly create front ends for their users to run their code and projects
Basic knowledge
The students must install MATLAB on their computers
The course is self explainatory and do not need any prior knowledge of MATLAB
What you will learn
You are able to confidently use MATLAB for problem solving
You are able to run scripts, write code and do data analysis and visualization
You are able to solve equations, do math operations and manipulate matrices in different ways
You are able to formulate your own logic and convert complex problems into MATLAB code and solve them using programming skills

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/developmenttool/complete-matlab-tutorial-go-from-beginner-to-pro
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Matplotlib

Course Description:

This course is meant to introduce people who have no programming experience to the world of computer science. With the tech industry becoming one of the most trending fields in the job market, learning how to program can be one of the most important and meaningful skills. This course will teach the basic, foundation concepts of programming in an easy-to-follow manner.

The first part of the course will get students acquainted with some basic concepts used in programming and will lay the conceptual groundwork that the rest of the course will build upon. After learning the basic terms and concepts of computer programming, the next two sections of the course allow students to practice these concepts hand-on.

Students will follow along with basic examples in two programming languages: Python and JavaScript. Both languages are easy for beginners to learn and are very user friendly. This course won’t make you an expert programmer, but it will give you an exciting first look at programming and a foundation of basic concepts with which you can start your journey learning computer programming.

Who is the target audience?

Anyone with little to no programming experience.
Anyone who wants to learn to code.
Anyone who wants to learn programming but doesn't know where to start.
Basic knowledge
You don't need any prior programming knowledge or experience
You should be able to use a PC at beginner level.
What you will learn
Learn the basic concepts used in Computer Programming.
Create basic programs using Python and JavaScript.
Get hands-on, step-by-step experience writing code.

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/javascript/computer-programming-for-beginners
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
JavaScript

Course Description:

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data.

This course is a zoom-in, zoom-out, hands-on workout involving Hadoop, MapReduce and the art of thinking parallel.

Let’s parse that.

Zoom-in, Zoom-Out: This course is both broad and deep. It covers the individual components of Hadoop in great detail, and also gives you a higher level picture of how they interact with each other.

Hands-on workout involving Hadoop, MapReduce : This course will get you hands-on with Hadoop very early on. You'll learn how to set up your own cluster using both VMs and the Cloud. All the major features of MapReduce are covered - including advanced topics like Total Sort and Secondary Sort.

The art of thinking parallel: MapReduce completely changed the way people thought about processing Big Data. Breaking down any problem into parallelizable units is an art. The examples in this course will train you to "think parallel".

What's Covered: Lot's of cool stuff ..

Using MapReduce to:

Recommend friends in a Social Networking site: Generate Top 10 friend recommendations using a Collaborative filtering algorithm.

Build an Inverted Index for Search Engines: Use MapReduce to parallelize the humongous task of building an inverted index for a search engine.

Generate Bigrams from text: Generate bigrams and compute their frequency distribution in a corpus of text.

Build your Hadoop cluster:

Install Hadoop in Standalone, Pseudo-Distributed and Fully Distributed modes

Set up a hadoop cluster using Linux VMs.

Set up a cloud Hadoop cluster on AWS with Cloudera Manager.

Understand HDFS, MapReduce and YARN and their interaction

Customize your MapReduce Jobs:

Chain multiple MR jobs together

Write your own Customized Partitioner

Total Sort : Globally sort a large amount of data by sampling input files

Secondary sorting

Unit tests with MR Unit

Integrate with Python using the Hadoop Streaming API

.. and of course all the basics:

MapReduce : Mapper, Reducer, Sort/Merge, Partitioning, Shuffle and Sort

HDFS & YARN: Namenode, Datanode, Resource manager, Node manager, the anatomy of a MapReduce application, YARN Scheduling, Configuring HDFS and YARN to performance tune your cluster.

Using discussion forums

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

Yep! Analysts who want to leverage the power of HDFS where traditional databases don't cut it anymore

Yep! Engineers who want to develop complex distributed computing applications to process lot's of data

Yep! Data Scientists who want to add MapReduce to their bag of tricks for processing data

Basic knowledge
You'll need an IDE where you can write Java code or open the source code that's shared. IntelliJ and Eclipse are both great options.
You'll need some background in Object-Oriented Programming, preferably in Java. All the source code is in Java and we dive right in without going into Objects, Classes etc
A bit of exposure to Linux/Unix shells would be helpful, but it won't be a blocker
What you will learn
Develop advanced MapReduce applications to process BigData
Master the art of "thinking parallel" - how to break up a task into Map/Reduce transformations
Self-sufficiently set up their own mini-Hadoop cluster whether it's a single node, a physical cluster or in the cloud.
Use Hadoop + MapReduce to solve a wide variety of problems : from NLP to Inverted Indices to Recommendations
Understand HDFS, MapReduce and YARN and how they interact with each other
Understand the basics of performance tuning and managing your own cluster

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/hadoop/learn-by-example-hadoop-mapreduce-for-big-data-problems
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Hadoop

Course Description:

Prerequisites: Working with HBase requires knowledge of Java

Record and run settings a team which includes 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scale data processing jobs.

Relational Databases are so stuffy and old! Welcome to HBase - a database solution for a new age.

HBase: Do you feel like your relational database is not giving you the flexibility you need anymore? Column oriented storage, no fixed schema and low latency make HBase a great choice for the dynamically changing needs of your applications.

What's Covered:

25 solved examples covering all aspects of working with data in HBase
CRUD operations in the shell and with the Java API, Filters, Counters, MapReduce
Implement your own notification service for a social network using HBase
HBase and it’s role in the Hadoop ecosystem, HBase architecture and what makes HBase different from RDBMS and other Hadoop technologies like Hive
Using discussion forums
Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(
We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices
The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person.* The truth is, direct support is hugely expensive and just does not scale.
We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose
It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

Yep! Anyone who is interested in understanding HBase, NoSQL and distributed database management
Yep! Engineers who want to move away from RDBMS and use HBase for their database solution
Yep! Folks who are using Hadoop ecosystem tools for analytical processing and want a single system for both OLAP and OLTP
Basic knowledge
You'll need to have an IDE where you can run Java code, Intellij IDEA and Eclipse are both good options
You'll need to have some experience with Java programming
What you will learn
Set up a database for your application using HBase
Integrate HBase with MapReduce for data processing tasks
Create tables, insert , read and delete data from HBase
Get an all round understanding of HBase and it's role in the Hadoop ecosystem

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/hadoop/learn-by-example-hbase-the-hadoop-database
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Hadoop

Course Description:

Image Processing Applications on Raspberry Pi is a beginner course on the newly launched Raspberry Pi 3 and is fully compatible with Raspberry Pi 2 and Raspberry Pi Zero.

The course is ideal for those who are new to the Raspberry Pi and want to explore more about it.

You will learn the components of Raspberry Pi, connecting components to Raspberry Pi, installation of NOOBS operating system, basic Linux commands, Python programming and building Image Processing applications on Raspberry Pi.

This course will take beginners without any coding skills to a level where they can write their own programs.

Basics of Python programming language are well covered in the course.

Building Image Processing applications are taught in the simplest manner which is easy to understand.

Users can quickly learn hardware assembly and coding in Python programming for building Image Processing applications. By the end of this course, users will have enough knowledge about Raspberry Pi, its components, basic Python programming, and execution of Image Processing applications in the real time scenario.

The course is taught by an expert team of Electronics and Computer Science engineers, having PhD and Postdoctoral research experience in Image Processing.

Anyone can take this course. No engineering knowledge is expected. Tutor has explained all required engineering concepts in the simplest manner.

The course will enable you to independently build Image Processing applications using Raspberry Pi.

This course is the easiest way to learn and become familiar with the Raspberry Pi platform.

By the end of this course, users will build Image Processing applications which includes scaling and flipping images, varying brightness of images, perform bit-wise operations on images, blurring and sharpening images, thresholding, erosion and dilation, edge detection, image segmentation. User will also be able to build real-world Image Processing applications which includes real-time human face eyes nose detection, detecting cars in video, real-time object detection, human face recognition and many more.

The course provides complete code for all Image Processing applications which are compatible on Raspberry Pi 3/2/Zero.

Who is the target audience?

Anyone who wants to explore Raspberry Pi and interested in building Image Processing applications
Basic knowledge
Only High School Maths
No prior programming knowledge is expected
All the code files and images used in this course will be provided
Hardware needed: Raspberry Pi 3/2/Zero, Monitor, Mouse, Keyboard, HDMI-VGA connector, USB flash drive (minimum storage capacity 2 GB), Micro SD card (minimum storage capacity 8 GB), Micro SD card reader, Power adapter (2 Amp, Micro-USB charger is preferred), USB Webcam (minimum 5 Megapixel resolution)
What you will learn
What is Raspberry Pi? and what are its components?
Understand peripherals that need to be connected to Raspberry Pi
Wire up your Raspberry Pi to create a fully functional computer
Easily learn preparing SD Card to load Operating System for Raspberry Pi
Install packages needed to build Image Processing applications
Learn basic programming aspects of Python
Create simple Image Processing applications using Python and OpenCV
Build real-world Image Processing applications on Raspberry Pi

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/python/image-processing-applications-on-raspberry-pi-from-scratch
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Python

Course Description:

This course introduces Python programming as a way to have hands-on experience with Data Science. It starts with a few basic examples in Python before moving onto doing statistical processing. The course then introduces Machine Learning with techniques such as regression, classification, clustering, and density estimation, in order to solve various data problems.

Basic knowledge
This course is for beginners, but it helps to have some basic understanding of statistics (mean, median, scatter plot) and preliminary knowledge of any programming. The course also assumes that you know how to download and install various programs/apps, and you are able to edit and debug simple programs
What you will learn
Writing simple Python scripts to do basic mathematical and logical operations
Loading structured data in a Python environment for processing
Creating descriptive statistics and visualizations
Finding correlations among numerical variables
Using regression analysis to predict the value of a continuous variable
Building classification models to organize data into pre-determined classes
Organizing given data into meaningful clusters
Applying basic machine learning techniques for solving various data problems

Gmail: support@simpliv.com
Phone no: 5108496155

Click to Continue Reading: https://www.simpliv.com/search
Registration Link: https://www.simpliv.com/machinelearning/introduction-to-data-science-with-python
Simpliv Youtube Course & Tutorial : https://www.youtube.com/channel/UCZZevQcSlAK689KbsrMvEog?
Facebook Page: https://www.facebook.com/simplivllc
Linkedin: https://www.linkedin.com/company/simpliv
Twitter: https://twitter.com/simplivllc

Subjects:
Machine Learning