Beneficial Information

*The Parable of the Coffee Bottle* ________________ A young couple had neighbours who were senior citizens, the husband around 80 years old, and the wife about 5 years younger.  The young couple were very fond of the elderly couple and made it a point to visit them and have coffee with them every Sunday. They observed that the old lady would bring the coffee bottle to her husband to be opened, every time. The thoughtful young man gifted the lady a gadget, without her husbands knowledge, to easily open the bottle, and showed her how to use it. On their next visit, the old lady once again brought the bottle for her husband to open! The young couple was amazed! Had she forgotten about the gadget?!  When the opportunity arose to be alone with the old lady, they quizzed her about this. Her reply made them speechless...... She said: "Oh, I can open the bottle myself, even without your gadget! But I get him to open it so he feels he is still stronger than I am and thus the man of our hom

*CAUTION - IMPORTANT MESSAGE* Many of them are forwarding a message to download an app that checks your blood oxygen level. We know that, low oxygen level can be an indicator for Covid infection. Be careful, incase you get a link to download such APPS to check your Oxygen levels.   *"Yes" People will fall prey to this quickly*, because of the current crisis (Covid19) where good health and safety is of prime importance. *Remember, this is another Covid19 related cyber Crime*   Note that, your index finger (fingerprint) is used for various personal data authentication. Especially, for eWallet transactions and as an alternative to password for screen lock and apps.  It is risky, as these apps ask us to keep our finger on camera to compute the oxygen levels, where it can be misused by the hackers to steal our fingerprints. These apps also steal your personal photos and data as it asks for storage and gallery permissions during installation.  It can also read your SMS inbox and

Mechanical engineers research, design, develop, build, and test mechanical and thermal devices, including tools, engines, and machines. Mechanical engineers typically do the following: Analyze problems to see how mechanical and thermal devices might help solve the problem. Design or redesign mechanical and thermal devices using analysis and computer-aided design. Develop and test prototypes of devices they design. Analyze the test results and change the design as needed. Oversee the manufacturing process for the device. Mechanical engineers design and oversee the manufacturing of many products ranging from medical devices to new batteries. They also design power-producing machines such as electric generators, internal combustion engines, and steam and gas turbines as well as power-using machines, such as refrigeration and air-conditioning systems. Like other engineers, mechanical engineers use computers to help create and analyze designs, run simulations and test how a machine is likel

Machine Learning Scientist: Machine learning scientists research new methods of data analysis and create algorithms. Data Engineer: Data Engineers prepare the “big data” infrastructure to be analyzed by Data Scientists. They are software engineers who design, build, integrate data from various resources, and manage big data. Data Analyst: Data analysts utilize large data sets to gather information that meets their company’s needs. Data Consultant: Data consultants work with businesses to determine the best usage of the information yielded from data analysis. Data Architect: Data architects build data solutions that are optimized for performance and design applications. Applications Architect: Applications architects track how applications are used throughout a business and how they interact with users and other applications.

Big data is very quickly becoming a vital tool for businesses and companies of all sizes. The availability and interpretation of big data has altered the business models of old industries and enabled the creation of new ones. Data-driven businesses are worth $1.2 trillion collectively in 2020, an increase from $333 billion in the year 2015.  Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations.  As big data continues to have a major impact on the world, data science does as well due to the close relationship between the two.

Techniques Linear regression Logistic regression Support vector machine Clustering is a technique used to group data together. Dimensionality reduction is used to reduce the complexity of data computation so that it can be performed more quickly. Machine learning is a technique used to perform tasks by inferencing patterns from data.

Python is a programming language with simple syntax that is commonly used for data science. There are a number of python libraries that are used in data science including numpy, pandas, and scipy. R is a programming language that was designed for statisticians and data mining and is optimized for computation. Julia is a high-level, high-performance, dynamic programming language well-suited for numerical analysis and computational science.

Framework *     Tensor flow is a framework for creating machine learning models developed by Google Pytorch is another framework for machine learning developed by Facebook. Jupyter notebook is an interactive web interface for Python that allows faster experimentation. Apache Hadoop is a software framework that is used to process data over large distributed systems. Visualization Tools Plotly provides a rich set of interactive scientific graphing libraries. Tableau makes a variety of software that is used for data visualization. PowerBI is a business analytics service by Microsoft.

Data Science online course by Harvard University Course benefits Fundamental R programming skills Statistical concepts such as probability, inference, and modeling and how to apply them in practice Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio Implement machine learning algorithms In-depth knowledge of fundamental data science concepts through motivating real-world case studies Advantages: ience HarvardX What you will learn Fundamental R programming skills Statistical concepts such as probability, inference, and modeling and how to apply them in practice Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio Implement machine learning  Duration

Introduction to Computer Science An introduction to the intellectual enterprises of computer science and the art of programming. Length: 12 Weeks  Effort: 6–18 hours per week   Institution Harvard university Level: Introductory Language: English Course Type: Self-paced on your time An entry-level course taught by David J. Malan,  CS50x  teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming.

Difference between peace and piece Peace   (Noun)   =   No   disturbance. Synonyms:   Calm,   Hush,   Quiet,   Solitude,   Tranquility Example:   Peace   is   not   merely   a   distant   goal   that   we   seek,   but   a   means   by   which   we   arrive   at   that   goal. Piece   (Noun)   =   A   portion   of   an       object Synonyms:   Chip,   Chunk,   Lump,   Segment,   Shred,   Slice Example:   In   anger   he   tore   important   papers   into   pieces .

If   two   subjects   are   of   different   numbers,   then     different   forms   of   ‘to   be’   or   ‘have’   auxiliaries  should   be   used. Error:   Two   boys   were   /   intelligent   but   /   a   boy   dull.   And   the   correct   sentence   should   be: Two   boys   were   intelligent   but   a   boy   was   dull.

Meaning : Give off Meaning: Emit   pollution   or   something   unpleasant Expand Behave   in   a   way   that   makes   people   think   of   you Examples: The  traffic   police   stopped   the   vehicle   because   it   was   giving   off   a  l ot   of   black   smoke.

Correct usage of infinitive  Errors in using English language Some   verbs   such   as   appear,   seem,    forget,   fail,   happen,   etc.   are   followed   by   infinitives. Error:   He   forgot   /   that   he   should   /     bring   a   pen.   Correct usage of forgot in sentence He   forgot   to   bring   a   pen.

In   the   sentence   having   main   verb      ‘know’,   infinitive   is   not   used   just     after   it   but   is   used   after   using   appropriate   question   words   such   as     how   /   when   /   why   /   where. Example:   He   informed   me   /   that   he   knew   to   /   play   on   the   harmonium.   /   No   error Explanation:   As   per   the   rule   given   above   there   is   an   error   in   the   second   part   of   the   sentence,   question   word   ‘how’   should   be   used   after   main   verb   ‘knew’.   So,   insert   ‘how’   in   between   knew   and   to. Therefore   the   correct   sentence   should   be: He   informed   me   that   he   knew   how   to   play   on   the   harmonium.