How to Create a Privacy Policy for Website or Blog

The privacy policy is a legal statement that discloses the data, that consists of how user data is gathered, used or shared with any third parties.

The need for Privacy Policy
According to the information act, every website which collects user data must contain a privacy policy. Which defines how it collects user data and what type of data should be collected and how it can be used and where it can be used etc details must be consists of the privacy policy statement.

How to Create a Privacy Policy?
There are some free websites which generate a free privacy policy statement for your website.
The top 5 privacy policy generating websites are
Www.freeprivacypolicy.com
www.privacypolicygenerator.info
Www.shopify.in/tools/policy-generator
www.privacypolicies.com
www.termsandconditionstemplate.com/privacy-policy-generator/

How to Create a Blog Post and Page Post in Blogger

Steps for How to Post an Article in Blogger Account and How to Post a Page in Blogger Account.

Login into your blogger account and Select Posts option available on right side of the blogger account.

Now you get New Post option and click on it, now you can get an Article Writing screen.

In article writing section you need to write TITLE and  CONTENT  and need to add a label to create categories, after writing these options, now select publish.

Your Title will be Written Here

Your Content will be written Here

Your article will publish Successfully.

Essential Pages Must Have to Create a Professional Blog or Website| Blogging Challenge

Everyone wants their website or blog to be a professional and with a full of visitors but to create a professional blog or website, We need to add some important pages in blog or website.

In this article, I will explain what are those important pages every blog must and should have and what are the uses of those pages.

1. About Page:

What is About Page?

About page contains a brief description of your blog and what services you provide in the blog or what type of content available in a blog and some websites also provide details about the author in the about page.

What are the main points need to mention in about page:

• Blog or Website or Company Starting Date.
• Use of the Website.
• What are the services you provided?
• Other Related information to attract visitors.

Uses: When a new user or advertiser or some customer visits your blog and he likes your articles and services, but he also found the same type of content in another blog. In that time how he can finds which one is best, this problem solved by the about page and sometimes he wants to contact you so you also need to create a contact page.

2. Contact Page:

Contains you contact details such as email, address, phone no etc or contact form.

Uses: Which helps people to contact you when they have any queries or they need any information.

3. Advertising page

It is important to grow your blog and revenue. Don’t skip this one

What information you need to put there?
What are the advertising packages you offer and its cost, website traffic details, website rank etc information that needs to attract the advertisers to place his ads on your site or to promote his content on your site.

4. Sitemap / Archive

When you publish big amounts of content regularly. The sitemap or archive will help to visitors to sort your content easily and finds required content easily.

5. Privacy policy page

A Privacy Policy agreement is required by law if you’re collecting personal data from your users. This includes name, address, email, credit card details and so on.

A privacy policy is must for every website, a privacy policy tells to the visitor what type of details you can take from them how to use them ex: how any personal information and data (e.g. advertising, cookies, emails etc) you are collected from them how you use those data such as sharing with third parties or using emails for inbox notification etc.

6.Terms and Conditions Page

It important to protect your content. So you set rules to the visitor for using your website.

7. Affiliate Disclosure

You just need to create this page If you are promoting affiliate products on your site.

An affiliate disclosure is a disclaimer statement that tells to consumers that you are in a paid relationship with the Affiliate company or with a person.

Some Affiliate website rejects the application when the website does not have this statement.

How to Create a Blog Using Blogger | 90 Days Challenge | Day 1

To start a blog using Blogger, you need to have a google account, If you don't have google account create one else login with an existing account.

Step by Step Guide to Create a BLOG using BLOGGER

1. Visit this link blogger.com

2. Sign in to Blogger by click on SIGN IN option available on the top right most corner and login into account by using google account login details. if don't have an account, Create a new one by clicking on Create New Account.

After login into your account your account you get the screen like this. Blogger Profile Display Name

Create a Profile Name and Select Continue to Blogger. Now you get a screen like this

3. Now Click on CREATE NEW BLOG, you get a screen like this

4. Now Enter Title (means blog name) and Address (means Blog URL). Your URL looks like this getstudentnotes.blogspot.com, Don't worry we change it later to like this studentnotes.in and Select any one of the themes and click on Create a Blog.

5. Now your blog is Created Successfully. To see your blog click on view blog.
 Do this today, in the next article we learn more.

Note: If you have any DOUBTS. Comment below I will provide a solution to you as soon as possible and also provide a review about my post on the comment section.

[PDF] SOFTWARE PROJECT MANAGEMENT | SPM STUDENT NOTES | JNTU

 

JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTU)

(ML) MACHINE LEARNING  - STUDENT NOTES

PDF/DOC FREE DOWNLOAD

 

UNIT I Conventional Software Management:

Download: Google Drive LInk(Written Notes): Download

UNIT II Improving Software Economics:

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UNIT III Life cycle phases:
Download: Google Drive LInk(Written Notes): Download

UNIT IV Work Flows of the process:
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UNIT V Project Control and Process instrumentation:
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UNIT I
Conventional Software Management: The waterfall model, conventional  software Management performance. Evolution of Software Economics: Software Economics, pragmatic software cost estimation

UNIT II
Improving Software Economics: Reducing Software product size, improving software processes, improving team effectiveness, improving automation, Achieving required quality, peer inspections.
The old way and the new: The principles of conventional software engineering,
principles of modern software management, transitioning to an iterative process

UNIT III
Life cycle phases: Engineering and production stages, Inception, Elaboration,
construction, transition phases.
Artifacts of the process: The artifact sets, Management artifacts, Engineering
artifacts, programmatic artifacts. Model based software architectures: A Management perspective and technical perspective.

UNIT IV
Work Flows of the process: SoReference Books :
1. Applied Software Project Management, Andrew Stellman & Jennifer Greene,
O‟Reilly, 2006
2. Head First PMP, Jennifer Greene & Andrew Stellman, O‟Reilly,2007
3. Software Engineering Project Managent, Richard H. Thayer & Edward Yourdon,
second edition,Wiley India, 2004.
4. Agile Project Management, Jim Highsmith, Pearson education, 2004
5. The art of Project management, Scott Berkun, O‟Reilly, 2005.
6. Software Project Management in Practice, Pankaj Jalote, Pearson Education,2002ftware process workflows, Inter Trans workflows.
Checkpoints of the Process: Major Mile Stones, Minor Milestones, Periodic status assessments. Iterative Process Planning: Work breakdown structures, planning guidelines, cost and schedule estimating, Interaction planning process, Pragmatic planning.
Project Organizations and Responsibilities: Line-of-Business Organizations, Project Organizations, evolution of Organizations.
Process Automation: Automation Building Blocks, The Project Environment

UNIT V
Project Control and Process instrumentation: The server care Metrics, Management indicators, quality indicators, life cycle expectations pragmatic Software Metrics, Metrics automation. Tailoring the Process: Process discriminates, Example.
Future Software Project Management: Modern Project Profiles Next generation
Software economics, modern Process transitions.
Case Study: The Command Center Processing and Display System-Replacement
(CCPDS-R)

Text Books:
1. Software Project Management, Walker Royce, Pearson Education.
2. Software Project Management, Bob Hughes & Mike Cotterell, fourth edition,Tata Mc-Graw Hill

Reference Books :
1. Applied Software Project Management, Andrew Stellman & Jennifer Greene,
O‟Reilly, 2006
2. Head First PMP, Jennifer Greene & Andrew Stellman, O‟Reilly,2007
3. Software Engineering Project Managent, Richard H. Thayer & Edward Yourdon, second edition,Wiley India, 2004.
4. Agile Project Management, Jim Highsmith, Pearson education, 2004
5. The art of Project management, Scott Berkun, O‟Reilly, 2005.
6. Software Project Management in Practice, Pankaj Jalote, Pearson Education,2002

90 Days Blogging Challenge | How to Create 6 Figure Blog Using Blogger

Learn How to create a six-figure blog using blogger.com within 90 days
Before Going to the90 days Blogging Challenge. First, we need to create an Account in Blogger.com, Which is a Google Free Blogging Service, If you have a Google account no need to create a new account. That is enough to start a blog with blogger

To Promote your blog you need to create a Facebook Page, Twitter, and Instagram account. If you don't know how to create these, I told later.
Tomorrow, I started the challenge to create 6 figure blog to learn with us, and to start the challenge with us follow our profile on UC We-Media to read our articles regularly or follow our blog studentnotes.in.

[PDF]&[PPT] MACHINE LEARNING NOTES | ML STUDENT NOTES | JNTU

 JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTU)

(ML) MACHINE LEARNING  - STUDENT NOTES

PDF/DOC FREE DOWNLOAD

  

Unit I:What is Machine Learning?: 

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Unit 2: Evaluating Hypotheses:

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Unit 3: Dimensionality Reduction:
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Unit 4: Linear Discrimination:
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Unit 5: Kernel Machines:
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MACHINE LEARNING (Single PDF) All Topics:

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MACHINE LEARNING  SYLLABUS

Unit I:What is Machine Learning?, Examples of machine learning applications, supervised Learning: learning a class from examples, Vapnik- Chervonenkis dimension, probably approximately correct learning, noise, learning multiple classes, regression, model selection and generalization, dimensions of a supervised machine learning algorithm. Decision Tree Learning: Introduction, Decisions Tree representation, Appropriate problems for decision tree learning, the basic decision tree learning algorithm, Hypothesis space search in decision tree learning, Inductive bias in decision tree learning, issues in decision tree learning, Artificial Neural Networks: Introduction, Neural Network  Representation – Problems – Perceptrons – Multilayer Networks and Back Propagation Algorithm, Remarks on the BACKPROPGRATION Algorithm, An illustrative Example: Face Recognition, Advanced Topics in Artificial Neural  Networks.

Unit 2: Evaluating Hypotheses: Motivation, Estimating hypothesis accuracy, basics of sampling theory, a general approach for deriving confidence intervals, differences in error of two hypothesis, comparing learning algorithms, Bayesian Learning: Introduction, Bayes Theorem, Bayes Theorem and Concept Learning, Maximum Likelihood and least squared error hypothesis, Maximum Likelihood hypothesis for predicting probabilities, Minimum Description Length Principle, Bayes Optimal Classifier, Gibbs Algorithm, Naïve Bayes Classifier , Bayesian Belief Network, EM Algorithm

Unit 3: Dimensionality Reduction: Introduction, Subset selection, principle component analysis, feature embedding, factor analysis, singular value decomposition and matrix factorization, multidimensional scaling, linear discriminant analysis, canonical correlation analysis, Isomap, Locally linear embedding, laplacian eigenmaps, Clustering: Introduction, Mixture densities, K- Means clustering, Expectations- Maximization algorithm, Mixture of latent variable models, supervised learning after clustering, spectral clustering, Hierarchal clustering, Choosing the number of clusters, Nonparametric Methods: Introduction, Non Parametric density estimation, generalization to multivariate data, nonparametric classification, condensed nearest neighbor, Distance based classification, outlier detection, Nonparametric regression: smoothing models, how to choose the smoothing parameter

Unit 4: Linear Discrimination: Introduction, Generalizing the linear model, geometry of the linear discrimination, pair wise separation, parametric discrimination revisited, gradient descent, logistic discrimination, discrimination by regression, learning to rank, Multilayer Perceptrons: Introduction, the perceptron, training a perceptron, learning Boolean functions, multilayer perceptrons, MLP as a universal approximator, Back propagation algorithm, Training procedures, Tuning the network size, Bayesian view of learning, dimensionality reduction, learning time, deep learning

Unit 5: Kernel Machines: Introduction, Optimal separating hyperplane, the non separable case: Soft Margin Hyperplane, ν-SVM, kernel Trick, Vectorial kernels, defining kernels, multiple kernel learning, multicast kernel machines, kernel machines for regression, kernel machines for ranking, one-class kernel machines, large margin nearest neighbor classifier, kernel dimensionality reduction, Graphical models: Introduction, Canonical cases for conditional independence, generativeUnit 5: Kernel Machines: models, d separation, belief propagation, undirected Graphs: Markov Random files, Learning the structure of a graphical model, influence diagrams.

Text Books:
1) Machine Learning by Tom M. Mitchell, Mc Graw Hill Education, Indian Edition, 2016.
2) Introduction to Machine learning, Ethem Alpaydin, PHI, 3 rd Edition, 2014

References Books:

1) Machine Learning: An Algorithmic Perspective, Stephen Marsland, Taylor & Francis,CRC Press Book,



@Credits: Syllabus Taken From JNTU