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To add static files(css, js files, images) some basic changes are made in django files as per given below code files: First we create html file by creation directory 'templates' in our in app folder like this: And then after create html files(index.html). Go to the setting.py file and make changes in this file like this: TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] After adding this code TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR,'TEMPLATES')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] Create another directory static in Appfolder(helloworld) in create any static files(like css, js, image) inside it: Add css file: To insert CSS file in project first create a directory in main project folder whose name is static. After that some changes are made to run the code. First add this load code at the top of of index.html page: {% load static %} After this go to the setting.py and changes in the static part which is located at the last in the setting.py file: # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' STATICFILES_DIRS = [ os.path.join(BASE_DIR,'static') ] And run the project. Project 1: Print Hello world: url.py: First set path in url.py from django.contrib import admin from django.urls import path from helloworld.views import Hello urlpatterns = [ path('admin/', admin.site.urls), path('helloworld/',Hello) //set path ‘helloword/’and pass Hello method ] Views.py: After set path in url.py make changes in views.py file. from django.http import HttpResponse def Hello(request): //add method hello return HttpResponse("Hello") # Create your views here. Setting.py: Add app name to the setting.py file: INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'helloworld', //app name ] If you like Codersarts blog and looking for Assignment help, Project help, Programming tutors help and suggestion you can send mail at contact@codersarts.com. #Howtoaddcssfileindjangoprojet #Djangoassignmenthelp #Djangoprojecthelp #Djangohomeworkhelp #Howtocreatedjangoapp #createdjangoapp #Djangohelpinusa #Howaddstaticfilesindjango

MongoDB stores data in JSON-like documents, which makes the database very flexible and scalable. To be able to experiment with the code examples in this tutorial, you will need access to a MongoDB database. You can download a free MongoDB database at https://www.mongodb.com. How to install MongoDB ? Go to the official website https://www.mongodb.com Click Try free at right corner as per given screenshot: And after this choose server button. Choose OS, and package MIS and after this click on download button. Click next button: Accept term and condition, and then click on next button: Select Choose setup type: complete: Click on next without changes anything: Again Click next Installation started..... After MongoDB installation successfully finish you click Finish button on next window. Go to the Program files ->MongoDB->bin Copy the path and go to the command prompt and paste the path as like and press enter and follow the steps as per given screenshot: After this type mongod command in your cmd command prompt and press Enter. Server installation started: Some exception raise regarding path to create data->db inside C directory. And after run mongod command to run server. Open Another command prompt. And run again: cd C:\Program Files\MongoDB\Server\4.0\bin press enter and run mongo command on cmd command prompt. After this to show all previous database inside use command >Show dbs Output: it exist default database inside Admin 0.000GB Config 0.000GB Local 0.000GB Create our database use use command as: >use naveen press enter Switched to db Naveen >Show dbs Admin 0.000GB Config 0.000GB Local 0.000GB Not show naveen database because not inserted data so insert data use this command >db.books.insert({“name”:”mongo book”}) syntax: (db.name of collection.insert({“keyname”:”value”})) Press enter and create this collection: Result: WriteResult({“nInserted” : 1}) To show database use >show dbs Result: Admin 0.000GB Config 0.000GB Local 0.000GB Naveen 0.000GB To list out all the collection use this command >show collections; Result: inside the naveen database Books Show element inside books collection: >db.books.find() Result: {“_id” : ObjectId(“5cd….c1), “name” : “mongo book”} Close command prompt Again open Run mongodb from anywhere show error internal and external command so need to set environment variable: C:\users\naveen kumar\mongod press enter Error External and Internal command Set Environment Variable: Choose path where django installed (C:\Program Files\MongoDB\Server\4.0\bin) and go to system start window choose system and click Advanced system setting. And then click on Environment Variable. In system variable box find path double click on it. Click on new and add this path: C:\Program Files\MongoDB\Server\4.0\bin Now you can run anywhere by cmd like no need to give complete path. C:\users\naveen kumar\mongodb press enter In next blog we will provide some example with running screenshot. For more details go to the mongodb official website. For any issue regarding Assignment contact here. #MongoDBassignmenthelp #MongoDBhomeworkhelp #MongoDBExperthelp #Databaseassignmenthelpwithmongodb #MongoDBdatabaseassignmenthelp #Mongodbprojecthelp #Mongodbprojectandhomeworkhelp #Mongodbwebpageexperthelp #HowtoinstallMongodb #Howrunmongodbprojectinshellscript #MongoDBassignmentandexperthelp #Mongodbdatabaseassignmenthelpinshellscript

What is Python Django Framework? Django is Python Framework which is used to create web development project . It’s quick & easy to get up and running with Django. Python is the buzzword that is making the rounds in the IT universe with the easy learning curve, application development being quicker and faster, added benefit of machine learning aided opportunities and what not. History of Python Django Framework Django was created in the fall of 2003, developed by Lowrence Journal. It was released publicly under a BSD license in July 2005. In June 2008, it was announced that a newly formed Django Software Foundation(DSF). Why Django is important in Python Assignment Help? With Django, you can take Web applications from concept to launch in a matter of hours. Django takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. It’s free and open source. What official definition say about Django: Django was invented to meet fast-moving newsroom deadlines, while satisfying the tough requirements of experienced Web developers. A web framework or a library is one that helps make the developer’s life easy with the whole process of development. With that context, let us go through the following Python frameworks and understand what they have to offer and why one should opt to work with these frameworks. Key features of Django Ridiculously fast: Django was designed to help developers take applications from concept to completion as quickly as possible. Fully loaded: Django includes lots of extras you can use to handle common Web development tasks. Django takes care of user authentication, content administration, site maps, RSS feeds, and many more tasks — right out of the box. Reassuringly secure: Django takes security seriously and helps developers avoid many common security mistakes, such as SQL injection, cross-site scripting, cross-site request forgery and clickjacking. Its user authentication system provides a secure way to manage user accounts and passwords. Exceedingly scalable: Some of the busiest sites on the planet use Django’s ability to quickly and flexibly scale to meet the heaviest traffic demands. Incredibly versatile: Companies, organizations and governments have used Django to build all sorts of things — from content management systems to social networks to scientific computing platforms. MVT Support: Django is a MVT(Model, view and template) model Python Django Assignment Help by Codersarts.com Codersarts is a top rated website for students which is looking for online Programming Assignment Help of Python Django Assignment Help to students at all levels whether it is school, college and university level Coursework Help or Real time Django project. Hire us and Get your projects done by Django expert developer or learn from Python expert with team training & coaching experiences. Our Django expert will provide help in any type pf programming Help, tutoring,  Django project development Areas covered in Python Django Assignment By Codersarts: Django Assignment Help for computer science students Python Programming project Help for Computer Science Engineering student, MCA students, and other Computer related courses assignment help for all semester Online Python Django tutorial for learner and developer, we have attached tutorial link here Learn Django and boost project skills Blog site app creation or developing Get readymade project, if you not have a time or deadline is too close API Using Flask Migration from one database to another using python Django Let's see more about Django Coding and Programming flavour. Why learn Django? Before learn any technology first it is important that why we learn it. Django has many reason to learn it because it is the python framework, python is a powerful language now a day it covers all the areas like Data Science and AI. It is this easy to migrate to any programming language. Features of Django with Python Programming Documentation: Most of developer and companies preferred the Django framework because it provides a structured documentation than the other framework in the market. Documentation make easy to understand and learn about any technologies so if documentation is easy and organized then it make easy to maintain any web application. High scalability: Scalability means that at what scope or level, our technology gets to implement. For bigger websites like Instagram, there are lots of active users (millions of them) which generate data in huge amounts (terabytes of data/day). Versatile: Django is versatile in nature because it provides us with a solid foundation which can then be used to make whichever application we want to create. It allows extending Django with all the technologies we work with and also with the upcoming ones. Therefore, Django is the future of web development and everyone who was previously using PHP will majorly use Django Secure: Django is highly secure than the other framework because it covers the loopholes by default. Although while using Django you may not feel it but those expert backend developers can tell the quality and security of the work done by Django. Provide rapid development: Django provide rapid development facility than the other. Here, rapid development means that we won’t need expert backend knowledge to make a fully functional website. We will also not create separate server files to design the database and connect the same while also making another file for transferring data to and from the server. Django Model -MVT This is the modification of MVC architecture although Django core architecture is based on MVC but in MVT implementing some variation of MVC architecture. MVT Architecture components MVT architecture divided into three components ​ Model Model contains logical file structure of projects. It contains all class related to modes and it the middleware of View and Templates. It provides a definition of how data information as coming from the View. Creating Django Model First create an app using previous command and then open models.py file: ​ from django.db import models class MyModelName(models.Model): # Fields            field_name = models.CharField(max_length=20, help_text='Enter field documentation') ... # Metadata class Meta:        ordering = ['-field_name'] In next we read what is view and how it work. ​ View The View in MTV architecture can look like the controller, but it’s not. The View in this MTV architecture is formatting the data via the model. In turn, it communicates to the database and that data which transfer to the template for viewing. There are two types of view which used to develop any web application: Class based views Function based views ​ Templates Templates is the life of developer to developer front end of the any web applications it contains the all information related to static files like media, css, javascript and HTML files. Python Frameworks In python three types of frameworks which used by most of developer Django Flask Pyramid Django is a set of all of these libraries and lots of different things too so you could mainly concentrate on precisely what your application does rather of other boiler plate things such as these. Before start the Django framework first install it, Here some steps to install Django framework in our PC. Installation Installation in Windows: First go to the start menu on and click on run, type cmd. And then enter Install using pip: Write this command on cmd command prompt >pip install django==2.2 After installation setup path at which you want setup projects by using cd command as: C:\Users\naveen kumar\cd paste here new path For example: To start new project: Paste it by using cd command at command prompt >django-admin startproject myproject Where myproject is your project name depend upon your choice. Create application inside myproject: open Pycharm and paste our project path as per given screenshot: Click ok button and wait for loading file: If already old project here than open it in new window if popup is show. Now you are ready to start the new Django App run this command on cmd: >C:\Users\naveen kumar\nawproject\djangoproject\myproject>python manage.py startapp HelloworldApp Here HelloworldApp is your app name. Run before setting username >Python manage.py migrate Set Username password for Admin panel : BY past this in command prompt >Python manage.py createsuperuser Starting server: Go to the command prompt and run this to start server >Python manage.py runserver Now your server is running provide the url copy and past it on your browser. Your our Installation process is finish. In next blog we will discussing how to make a project by using django. For more details click here... To understand it here we explain complete small app by using pycharm- Example "HellowordApp" Structure of this- To start this first we see the basic structure of this app Workflow with coding for Windows User >django-admin startproject HelloWordApp Go to the projectname directory then run this to create and app >python manage.py startapp helloworld ​ Running the Test Server >python manage.py runserver Next we will do complete coding part step by step. First open setting.py file which located at HelloWordApp project folder, add app name at last of INSTALLED_APPS part. setting.py: ​ INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'helloworld' ] ​ In above code bold part is appname. Now we go to the view.py which exist at project app folder helloworld. ​ view.py: ​ #from django.shortcuts import render from django.http import HttpResponse def Hello(request): return HttpResponse("Hello") ​ Now go to the urls.py and set urls path. ​ urls.py: ​ from django.contrib import admin from django.urls import path #from helloworld.views import Index from helloworld.views import Hello urlpatterns = [ path('admin/', admin.site.urls), #path('helloworld/',Index), path('helloworld/',Hello) ] After this you can run from terminal or cmd by using running below command >python manage.py runserver And you will find url like this and open it on browsers and run. ​ Django version 2.2.1, using settings 'HelloWordApp.settings' Starting development server at http://127.0.0.1:8000/ Quit the server with CTRL-BREAK. Not Found: / Now you find output window after running this url with app name as a path like http://127.0.0.1:8000/helloworld Output Oh ! it is running properly. 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For beginners it’s simple, start with Python because it is easy to learn and powerful enough to build a web application. But it not a enough to satisfied the concept of , why we learn python?? Here codersarts expert help give some reason to clarify the concept of why we learn python?? learn python. Here codersarts expert help team give 10 reasons to learn Python in 2019: 1.Data science: This is the single, biggest reason why many programmers are learning Python in 2019. ​ Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning. 2.Machine learning: This is another reason why programmers are learning Python in 2019. The growth of machine learning is phenomenal in last a couple of years and it’s rapidly changing everything around us. 3.Web development: The good old development is another reason for learning Python. It offers so many good libraries and frameworks e.g. Django and Flask which makes web development really easy. 4. Simplicity: Easier to learn which keeps you going to learn anything and everything in Python 5.Value and demand: Python is being used by many big companies as it is simple, versatile and easy to maintain 6.Community: and open source: It is open source so you can get to know every aspect of it if you want. At the same time, Python is hugely popular and has a massive community of developers who can support you when you run into trouble. 7.Resources: In Python you often won’t need to write much code because Python comes with great standard library. 8.Salary: Python developers are some of the highest paid developers, particularly in the fields of data science, machine learning, and web development. 9.Growth: Python is growing really fast and it makes a lot of sense to learn growing programming language if you are just starting your programming career. 10.Google use it: In fact Python is one of Google’s preferred languages, they are always looking to hire experts in it and they have created many of their popular products with it. l hope you enjoyed reading my blog and understood why we learn python. For any GUI or assignment related help visit here, that comes with instructor-led live training and real-life project experience. #pythonguihelp #pythonassignmenthelp #whywelearnpython #pythonassignmenthelpAUSTRALIA #onlinepythonassignmenthelp #onlinepythonprojecthelp #onlinepythonGUIhelp #onlinepythonwebapplicationassignment #pythonwebassignment #pythonwebapplication #programmingassigment

Codersarts expert help cover some topic pandas dataframs: Padas is a high-level data manipulation tool. It is built on the Numpy package. Pandas allow many way to create Dataframes, in which most Common DataFrames are- contact us By using Dictionary By importing csv file By using Dictionary: By importing csv file: Some observation perform on csv file Used some observation to edit the csv file which are given below: loc ( label-based) The loc indexer is used with the syntax as loc: iloc (integer index based) The iloc indexer is used with the same syntax as loc: display first row- If you like Codersarts blog and looking for Assignment help,Project help, Programming tutors help and suggestion you can send mail at contact@codersarts.com. Please write your suggestion in comment section below if you find anything incorrect in this blog post. #pythonexperthelp #pythonassignmenthelp #pythononlineassignmenthelp #assignmenthelp #pythondataframehelp #ilocinpython #locinpython #howtoimportcsvfileinpython #onlineexperthelp #pythonasssignmenthelp #ProgrammingAssignmentHelp

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Client-server using netcat. Open two computer terminals: The first will act as the server. The second will be the client. Syntax: nc [-options] hostname port[s] [ports] nc -l -p port [-options] [hostname] [port] Basic parameters: -l: set the “listen” mode, waits for the incoming connections. -p: local port -u: set the UDP mode TCP client With Netcat your PC will act like server Server: you want to begin as a server that listens at port 8080: $ nc -l 8080 In addition, we can use the server to connect to the port (8080) recently opened, from the client side: client: $ nc localhost 8080 #PythonTCP #pythonNetcat #runyourownserverusingnetcatinpythontcp

Command Line Arguments # Python provides a oldest one is the sys module. In terms of names, and its usage, it relates directly to the C library (libc). The second way is the getopt module which handles both short, and long options, including the evaluation of the parameter values.Furthermore, two lesser-known ways exist. The sys module implements the command line arguments in a simple list structure named sys.argv. # file name pythonScript.py #!/usr/bin/python import sys # Zero index points to the name of script file print ("Script file name: ", sys.argv[0]) # sys.argv is the list of arguments print ("The arguments are: " , str(sys.argv)) # length of arguments print ("Number of arguments: ", len(sys.argv)) sys.argv is the list of command-line arguments. len(sys.argv) is the number of command-line arguments. sys.argv[1], sys.argv[2], sys.argv[3] are argument 1,argument 2 and argument 3 respectively . Here sys.argv[0] is the program ie. script name. Example $ python pythonScript.py arg1 argv2 argv 3 Output: Script file name: pythonScript.py The arguments are: arg1 argv2 argv 3 Number of arguments: 4 #Python #pythontutorial #PythonCommandLineArguments #PythonCommandLineArguments

Are you looking for Apache Spark Assignment Help, Hadoop assignment help, Hadoop homework help?. Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs. Try Bigdata, Hadoop Assignment Help today : Getting started is easy. Are Big Data and Hadoop same? Big Data is nothing but a concept which facilitates handling large amount of datasets. Hadoop is just a single framework out of dozens of tools. Hadoop is primarily used for batch processing. The difference between big data and the open source software Hadoop is a distinct and fundamental one. Apache Spark is a unified analytics engine for large-scale data processing. Feature of Apache Spark Speed Apache Spark achieves high performance for both batch and streaming data Ease of Use Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Generality Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. Runs Everywhere Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. Apache Hadoop Architecture The Apache Hadoop framework comprises: Hadoop Common – Contains libraries and utilities needed by other Hadoop modules Hadoop Distributed File System (HDFS) – A distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster Hadoop YARN – A resource-management platform responsible for managing compute resources in clusters and using them for scheduling of users' applications Hadoop MapReduce– A programming model for large-scale data processing. Most popular framework for Big Data, Hadoop HDInsight (Hadoop) Assignment help Azure Machine Learning Studio Assignment help Homework help with Microsoft azure Big Data homework help with Azure Machine Learning #MachineLearningAssignmentHelp #Apachesparkassignmenthelp #BigdataAssignmenthelp #HadoopAssignmentHelp #Dataanalyticsinpython #HDInsightHadoopAssignmenthelp #HDInsightHadoophomeworkhelp #AzureMachineLearningStudioAssignmenthelp #HomeworkhelpwithMicrosoftazure #BigDatahomeworkhelpwithAzureMachineLearning #domymachinelearninghomeworkdomymachinelea

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Our Machine Learning expert is good at followings: Knowledge of Understanding ML models, along with metrics to track their progress to that help to achieve business objectives. Writing and Analyzing the best Machine learning algorithms fit for data that could be used to solve a given problem and ranking them by their success probability Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world Verifying data quality, and/or ensuring it via data cleaning Supervising the data acquisition process if more data is needed Have knowledge of tons of available datasets online that could be used for training Defining validation strategies Defining the preprocessing or feature engineering on a given dataset Defining data augmentation pipelines Training models and tuning their hyper-parameters Analyzing the errors of the model and designing strategies to overcome them Deploying models to production As Good Machine Learning expert the Skills you expect. Proficiency with a deep learning framework such as NLP, TensorFlow or Keras Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas Expertise in visualizing and manipulating big datasets Proficiency with OpenCV Familiarity with Linux Ability to select hardware to run an ML model with the required latency. What is machine Learning and How it works About this Machine Learning As a beginner in machine learning, You always struggle to first understand the basic concepts and algorithms includes an introduction to Regression, Classification Analysis and Support Vector Machines in Machine Learning apart from having general programming experience in C and Java and some knowledge on algorithms. Machine learning is just one aspect of data science. You also need to know how to properly load data, clean the data, extract features, and finally - perform machine learning model training and testing. Machine Learning is used in most critical applications, such as data mining, natural language processing, image recognition, and expert systems. That solves those problems that cannot be solved by numerical means alone. Through Machine Learning it is possible quickly and automatically produce models that can analyze bigger, more complex data and deliver faster with more accurate results even on a very large scale. Evolution of machine learning Machine Learning is not like the basic training and testing model it's improving day-by-day with new computation powers and advanced pattern recognition. At the beginning, machine learning was born from pattern recognition and learning algorithms from which computers can learn without being programmed to perform specific tasks with the help of data; Data Scientists or researchers wanted to see if computers could learn from data and predict for new data based trained data model. The repetitive iterative aspect on data to train model again and again is important because of new data. Here are a few most common widely examples of machine learning applications you may be familiar with: The heavily hyped, self-driving Google car? The essence of machine learning. Online recommendation offers such as those from Amazon and Netflix? Machine learning applications for everyday life. Knowing what customers are saying about you on Twitter? Machine learning combined with linguistic rule creation. Fraud detection? One of the more obvious, important uses in our world today. What's required to create good machine learning systems? Data preparation capabilities. Algorithms – basic and advanced. Automation and iterative processes. Scalability. Ensemble modeling How does it work? Machine Learning is very similar to human way of learning any skills for example you want to learn python programming for instant. For claiming yourself as python programmer you need to do these three things. Python Book, online course or Python training from Python expert( That means Data) You have to focus on learning and have to learn the concept thoroughly the better you under the better you'll be programmer that means you are training yourself how to solve problems.(Training the model i.e you mind in this case) and this is final step after you have completed the all python topics, you need to pass test or examination so that you can claim yourself that you are able to solve python programming problems comfortable. but suppose there you got 90 marks out of 100. that mean your grasp or understanding on python is 90% accurate. any be other student get 70, 80, 96,97, 90 etc. these different student are separate algorithms. Any student get higher marks have more feasible solution. And the highest marked student solving methods will be used for prediction in future and to verify learning python skills well. They are made up of three major parts, which are: Model, Parameters and Learner. The Basic definition is: A Model is the system that makes a prediction or assumption on solution. The Parameters are the signals or factors used by the model to make the right decisions. A Learner is a system that adjusts the parameters and in turns the model by looking at differences in predictions versus actual outcomes. Should I learn Python or R for machine Learning? Just toss a coin, heads: Python tails: R There is probably an even split between those who recommend  Python & those who recommend R - so you might as well toss a coin. Both Python or R, are easy to learn and focus on work rather than syntax. but why people love python is that you already had been learning python programming to do basic stuff, Django, Python GUI and other so you'll feel comfortable to need extra effort to learn basic syntax or programming construct. But in the case of R, you suddenly come in the world of new syntax and very fews people or student would have used R for basic programming task before. So i'll suggest in first go use python and in future if need R you can switch easily Just dive right in any start learning Machine Learning is the basis for the most exciting careers in data analysis today. Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies. Machine learning tasks are typically classified into two broad categories, depending on whether there is a learning "signal" or "feedback" available to a learning system: Supervised learning: The computer is presented with example inputs and their desired outputs, given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs. As special cases, the input signal can be only partially available, or restricted to special feedback: Semi-supervised learning: the computer is given only an incomplete training signal: a training set with some (often many) of the target outputs missing. Active learning: the computer can only obtain training labels for a limited set of instances (based on a budget), and also has to optimize its choice of objects to acquire labels for. When used interactively, these can be presented to the user for labeling. Reinforcement learning: training data (in form of rewards and punishments) is given only as feedback to the program's actions in a dynamic environment, such as driving a vehicle or playing a game against an opponent. Classification: Spam filtering of emails. Regression: These algorithms also learn from the previous data like classification algorithms but it gives us the value as an output Example: Weather forecast – as how much rain will be there? Clustering: These algorithms use data and give output in the form of clusters of data. Example: Deciding the prices of house/land in a particular area (geographical location). Association: When you buy products from shopping sites, the system recommends another set of products. Association algorithms are used for this recommendation Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning). Methods include in assignment help: Support vector machines linear and logistic regression Tree classifiers Boosting Maximum likelihood and MAP inference EM algorithm Hidden Markov models Kalman filters k-means Gaussian mixture models Among others. Topics include for assignment help: Classification and regression Clustering methods, sequential models Matrix factorization Topic modeling and model selection. Did you know? In machine learning, a target is called a label. In statistics, a target is called a dependent variable. A variable in statistics is called a feature in machine learning. A transformation in statistics is called feature creation in machine learning. Most Popular Machine Learning Software Tools There are several Machine Learning Software that is available in the market. Enlisted below are the most popular ones among them. Scikit Learn Platform: Linux, Mac OS, Windows Cost: Free Written in language: Python, Cython, C, C++Classification Algorithms or Features: Regression, Clustering, Preprocessing, Model Selection, Dimensionality reduction. PyTorch Platform: Linux, Mac OS,, Windows Cost: Free Written in language: Python, C++, CUDA Algorithms or Features: Autograd Module, Optim Module, nn Module TensorFlow Platform: Linux, Mac OS, Windows Cost: Free Written in language: Python, C++, CUDA Algorithms or Features: Provides a library for dataflow programming. Weka Platform: Linux, Mac OS, Windows Cost: Free Written in language: Java Algorithms or Features: Data preparation, Classification, Regression, Clustering, Visualization, Association rules mining KNIME Platform: Linux, Mac OS, Windows Cost: Free Written in language: Java Algorithms or Features: Can work with large data volume. Supports text mining & image mining through plugins Colab Platform: Cloud Service Cost: Free Algorithms or Features: Supports libraries of PyTorch, Keras, TensorFlow, and OpenCV Apache Mahout Platform: Cross-platform Cost: Free Written in language: Java, Scala Algorithms or Features: Preprocessors, Regression, Clustering ,Recommenders, Distributed Linear Algebra. Accors.Net Platform: Cross-platform Cost: Free Written in language: C# Algorithms or Features: Classification, Regression, Distribution, Clustering, Hypothesis Tests &, Kernel Methods, Image, Audio & Signal. & Vision Shogun Platform: Windows, Linux, UNIX, Mac OS Cost: Free Written in language: C++ Algorithms or Features: Regression, Classification, Clustering,Support vector machines. 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