Google on Thursday launched a new search engine for the scientific community that will help them make sense of millions of datasets present online. The service, called Dataset Search, will help scientists, data journalists and geeks find the data required for their work and their stories — or simply to satisfy their intellectual curiosity. The new search engine will work like Google Scholar, the company’s popular search engine for academic studies and reports.
Learn to create Machine Learning Algorithms in Python and R. This course is packed with practical exercises which are based on live examples. You’ll learn the theory and you’ll get some hands-on practice building your own models. Includes Python and R code templates to use on your own projects.
Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more. This course will give you a full overview of the Data Science journey. You’ll develop a good understanding of SQL, SSIS, Tableau, and Gretl.
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more. This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms.
When you finish this class, you’ll understand the major technology trends driving Deep Learning. Be able to build, train and apply fully connected deep neural networks. Know how to implement efficient neural networks. And understand the key parameters in a neural network’s architecture.
In this class, you’ll learn about the most effective machine learning techniques, and gain practice implementing them. You’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to apply these techniques to new problems.
Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. This training program is filled with intuition tutorials, practical exercises and real-world case studies.
There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
When learning to program you often have to sacrifice learning exciting and current technologies in favor of the “beginner friendly” classes. In this course, you get the best of both worlds. It’s designed for the beginner, yet covers some of the most exciting topics in the industry. Learn HTML, CSS, JS, Node, and more.
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If you have no technical background, don’t be afraid. This courses teaches you real-world SQL — not just the theory in abstract, but real skills you can use to get more data-driven in your current job. You’ll have the raw skills to do some real data analysis for your company using SQL.
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Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2. This training is packed with real-life analytical challenges which you will learn to solve. This course has been designed for all skill levels, no programming or statistical background needed.
This course begins with Tableau basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease. You’ll learn all of the features in Tableau that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully.
In the present world machine learning is one of the greatest invention for future.Today’s we can’t think about machine.In 2021 most of the powerful country has reputeted their power in machine learning.
There is a speech that-
“Artificial intellegence , Deep learning,Machine learning-whatever you are doing if you don’t understand it-learn it.Because otherwise you’re going to be a dianosour within 3 years”-Mark cuban
In 1959 Arthur samuel said-
Machine learning is a field science that gives computers the abaility to learn without being explicity programmed.
Samuel claim to fame was that back in the 1950’s he wrote a checkers playing program ,and the amazing thing about this checkers playing ptogram was that arthur samuel himself.but wasn’t good checkers player.But he had to ptogram to play 10’s to 1000’s games against itself.That was a remarkable result.
otherwise TomMitchell said
In 1998-
A computer program is said to learn from experience E with respect to some task T and some performance measure P,if its perfotmance on T as measured by P ,improves with experience E.
well as the most recent milestones.History of machine learning….
1950 — Alan Turing creates the “Turing Test” to determine if a computer has real intelligence. To pass the test, a computer must be able to fool a human into believing it is also human.
1952 — Arthur Samuel wrote the first computer learning program. The program was the game of checkers, and the IBM computer improved at the game the more it played, studying which moves made up winning strategies and incorporating those moves into its program.
1957 — Frank Rosenblatt designed the first neural network for computers (the perceptron), which simulate the thought processes of the human brain.
1967 — The “nearest neighbor” algorithm was written, allowing computers to begin using very basic pattern recognition. This could be used to map a route for traveling salesmen, starting at a random city but ensuring they visit all cities during a short tour.
1979 — Students at Stanford University invent the “Stanford Cart” which can navigate obstacles in a room on its own.
1981 — Gerald Dejong introduces the concept of Explanation Based Learning (EBL), in which a computer analyses training data and creates a general rule it can follow by discarding unimportant data.
1985 — Terry Sejnowski invents NetTalk, which learns to pronounce words the same way a baby does.1990s — Work on machine learning shifts from a knowledge-driven approach to a data-driven approach. Scientists begin creating programs for computers to analyze large amounts of data and draw conclusions — or “learn” — from the results.
1997 — IBM’s Deep Blue beats the world champion at chess.
2006 — Geoffrey Hinton coins the term “deep learning” to explain new algorithms that let computers “see” and distinguish objects and text in images and videos.
2010 — The Microsoft Kinect can track 20 human features at a rate of 30 times per second, allowing people to interact with the computer via movements and gestures.
2011 — IBM’s Watson beats its human competitors at Jeopardy.
2011 — Google Brain is developed, and its deep neural network can learn to discover and categorize objects much the way a cat does.
2012 – Google’s X Lab develops a machine learning algorithm that is able to autonomously browse YouTube videos to identify the videos that contain cats.
2014 – Facebook develops DeepFace, a software algorithm that is able to recognize or verify individuals on photos to the same level as humans can.
2015 – Amazon launches its own machine learning platform.
2015 – Microsoft creates the Distributed Machine Learning Toolkit, which enables the efficient distribution of machine learning problems across multiple computers.
2015 – Over 3,000 AI and Robotics researchers, endorsed by Stephen Hawking, Elon Musk and Steve Wozniak (among many others), sign an open letter warning of the danger of autonomous weapons which select and engage targets without human intervention.
2016 – Google’s artificial intelligence algorithm beats a professional player at the Chinese board game Go, which is considered the world’s most complex board game and is many times harder than chess. The AlphaGo algorithm developed by Google DeepMind managed to win five games out of five in the Go competition.
So are we drawing closer to artificial.
Machine learning algorithm:
Supervised Algorithm
-Linear regression
-Logistic regression
-Neural nework
-K-nearest neighbour algorithm
-Decision trees and random Forest
-SVM(support vactor machines)
Unsupervised algorithm
-Clustering
1.k-means
2.HCA
3.Expectation maximization
-Visualization and dimesionality reduction
1.PCA
2.kernal PCA
3.T-SNE
4.Locally linear embadding
-Associate rule learning
1.Apriori
2.Eclat
What is supervised learning-
Superised learning is a problem of taking data sets,gleaning information from it so that you can level new data set,machine learning task to learning a function to input to output pairs.
In one word says Function approximiately.
Supervised learning is prediction variable /features and a target variable.Supervised learning data consist of(x,y) pairs.In supervised learning problems we start with a data set containing training example with associated correct level.
Input - 1 2 3 4 5 6 7
Output-1 4 9 16 25 36 49
input-output square
Their two task of supervised learning-
1.Regression
2.Classification
Regression:Predict a continious numerical value.Target variable to continious.
Classification:Assign a level,target variable consist of categories.
Regression algorithm:Some of the most powerful regression algorithm is-
1.Logistic regression
2.linear regression
3.Polynomial regression
-Classification:The best classification algorithm is
Angular Js:
AngularJS is a structural framework for dynamic web apps. With AngularJS, designers can use HTML as the template language and it allows for the extension of HTML's syntax to convey the application's components effortlessly.
The following are the features of AngularJS:
Two-Way data binding
REST friendly
MVC-based Pattern
Deep Linking
Template
Form Validation
Dependency Injection
Localization
Full Testing Environment
Server Communication
Jquery:
jQuery is a fast and concise JavaScript Library created by John Resig in 2006. jQuery simplifies HTML document traversing, event handling, animating, and Ajax interactions for rapid web development.
The following are the features of Jquery:
jQuery is a library.
easily manipulate the contents of a webpage
Doesn’t supports two-way data binding.
easy DOM traversal
simple to make AJAX
Lightweight Footprint
CSS3 Compliant
Cross-Browser
It can be used on any website or web application
Bootstrap:
Bootstrap is an open source toolkit for developing with HTML, CSS, and JS. Quickly prototype your ideas or build your entire app with our Sass variables and mixins, responsive grid system, extensive prebuilt components, and powerful plugins built on jQuery.Ther are two version for now. Stable version 3.3.7 and preview version v4.0.0.
The following are the features of Bootstrap:
A CSS framework is a pre-prepared software framework that is meant to allow for easier, more standards-compliant web design using the Cascading Style Sheets language. Most of these frameworks contain at least a grid. Here Are Top five FrameWork List
1.Bootstrap
2. Zurb Foundation
3. Bulma
4.Materialize framework
5.Semantic UI
BootStarp
Bootstrap is an open source toolkit for developing with HTML, CSS, and JS. Quickly prototype your ideas or build your entire app with our Sass variables and mixins, responsive grid system, extensive prebuilt components, and powerful plugins built on jQuery.Ther are two version for now. Stable version 3.3.7 and preview version v4.0.0.
Website-click Zurb Foundation
Framework for any device, medium, and accessibility. Foundation is responsive front-end frameworks that make it easy to design beautiful responsive websites, apps, and emails that look amazing on any device. The framework is a mobile-first flexible, 12-column grid that can scale to an arbitrary size (defined by the max width of the row), customizable control handles, and pre-built layouts. Foundation is semantic, readable, flexible, and fully customizable. We're constantly adding new resources and code snippets, including these handy HTML templates to help get you started! Website-click Bulma
Bulma is an open source CSS framework based on Flexbox and used by more than 100,000 developers. Firstly, Bulma contains great UI components, like tabs, navigation bar, boxes, panel and much more because this framework is designed to provide you with clear and attractive UI. Secondly, Bulma is incredibly modular meaning you can import only those features that are needed and you can start your work. Finally, this framework has very readable classes, which again may be a huge advantage for some developers.
website-click
Materialize
Created and designed by Google, Material Design is a design language that combines the classic principles of successful design along with innovation and technology. Google's goal is to develop a system of design that allows for a unified user experience across all their products on any platform.
Website-click Semantic UI
Semantic UI is a modern front-end development framework, powered by LESS and jQuery. It has a sleek, subtle, and flat design look that provides a lightweight user experience.
Website-click
80 percent or more top websites use Javascript Since Javascript has such high acceptance and no competition, we can not really foresee Javascript going anywhere, anytime soon.JavaScript is becoming so popular. It is the only language that is understood by JS.
1. Server-side Scripting
2.Native Cross-Platform Support
3.Scalability
4.Easier Site Maintenance
5.Availability of Third Party Add-ons
Top Five Framework
Survey of stack overflow 62% Sectors Are Used JS
To Making This Website 66% Developer are working hard
1.Vue
Vue is a progressive framework for building user interfaces. Unlike other monolithic frameworks, Vue is designed from the ground up to be incrementally adopted. The core library is focused on the view layer only and is easy to pick up and integrates with other libraries or existing projects. On the other hand, Vue is also capable of perfecting the sophisticated Single-Page Applications when used in modern tooling and supporting libraries.
=> Components
=> Animation / Transition
=> Data Binding
2.React
React makes it painless to create interactive UIs. Design simple views for each state in your application, and React will efficiently update and render just the right components when your data changes.
Angular is a platform that makes it easy to build applications with the web. Angular combines declarative templates, dependency injection, an end to end tooling, and integrated best practices. Angular empowers developers to build applications that live on the web, mobile, or the desktop.
=> CROSS PLATFORM
=> SPEED AND PERFORMANCE
=> PRODUCTIVITY
=> FULL DEVELOPMENT STORY 4.Node.js
As an asynchronous event-driven JavaScript runtime, Node is designed to build scalable network applications. In the following "hello world" example, many connections can be handled concurrently. Upon every connection, the callback is fired, but if there is no work to be done, Node will sleep.
=> Asynchronous and Event Driven
=> Very Fas
=> Single Threaded but Highly Scalable
=> No Buffering 5.Ember.js
Ember.js is an open-source JavaScript web framework, based on the Model-view-ViewModel (MVVM) pattern. It allows developers to create scalable single-page web applications by incorporating common idioms and best practices in the framework.
=> Coherent Dev Tooling
=> Amazing Features
=> Integrates With Large Teams
HTML / CSS
HTML is the most basic building block you will need for developing website and CSS is the language used to style the document
Javascript
where HTML and CSS determine the content and presentation of the page, js determine the function.
CSS / javascript framework
CSS and JSF framework is the collection of the file that does not allow common functionality.
CSS preprocessor
CSS preprocessor lets you write code in preprocessor language and then converts that code to CSS.
Version control / git
version control software lets you track changes so you can go back to the previous version of your work and find out what's wrong.
Responsive design
responsive design allows to a webpage to adjust yourself to the device.
Testing / debugging
bugs are the reality of the development process so in order to keep thing moving you will need to test your code for bugs along the way.
Browser developer tools
Browser developer tools usually include an inspector (so you can see the HTML and CSS of the site) and a javascript console.
Web performance
the program like grunt and gulp can be used to automate image optimization CSS and js minifying and other web performance chores to make your website.
Command line
There will be times you need to open in the command line.
