top visual studio code extensions


Top 19 Most Used Visual Studio Code Extensions. I’ll be updating this list whenever I find something good.


There is curated list of resources at the end of this article. So read till the last line.


Here are my top picks for Visual Studio Code extensions for fullstack developers.


1. ESLint – The extension uses the ESLint library installed in the opened workspace folder. If the folder doesn’t provide one the extension looks for a global install version. If you haven’t installed ESLint either locally or globally do so by running npm install eslint in the workspace folder for a local install or npm install -g eslint for a global install.


2. Live Server – Launch a development local Server with live reload feature for static & dynamic pages.


3. Code Spell Checker! One nice thing is the extension understands camelCasePascalCasesnake_case, and more. Another great feature is there are dictionaries available for Spanish, French, German, Russian, and a number of other languages.


4. Settings Sync – Synchronize Settings, Snippets, Themes, File Icons, Launch, Keybindings, Workspaces and Extensions Across Multiple Machines Using GitHub Gist.


5. Bracket Pair Colorizer – A customizable extension for colorizing matching brackets.


6. Quokka – Live Scratchpad for JavaScript.


7. Live Share – Real-time collaborative development from the comfort of your favorite tools.


8. Code Spell Checker – Spelling checker for source code.


9. Prettier – Prettier is an opinionated code formatter. It enforces a consistent style by parsing your code and re-printing it with its own rules that take the maximum line length into account, wrapping code when necessary.


10. Auto Rename Tag – Automatically rename paired HTML/XML tag, same as Visual Studio IDE does.


11. Markdownlint extension can help you make sure your markdown syntax is in good form!


12. EditorConfig – This plugin attempts to override user/workspace settings with settings found in .editorconfig files. No additional or vscode-specific files are required. As with any EditorConfig plugin, if root=true is not specified, EditorConfig will continue to look for an .editorconfig file outside of the project.


13. Browser Preview – Browser Preview for VS Code enables you to open a real browser preview inside your editor that you can debug. Browser Preview is powered by Chrome Headless, and works by starting a headless Chrome instance in a new process.


14. Chrome Debugger – Debug your JavaScript code in the Chrome browser, or any other target that supports the Chrome Debugger protocol.


15. REST Client – REST Client allows you to send HTTP request and view the response in Visual Studio Code directly.


16. Import Cost – This extension will display inline in the editor the size of the imported package. The extension utilizes webpack with babili-webpack-plugin in order to detect the imported size.


17. Code Metrics – Computes complexity in TypeScript / JavaScript / Lua files.


18. DotENV extension for VS Code adds convenient syntax highlighting when editing a .env file.


19. Material Icon Theme adds a ton of icons to VS Code for different file types. Being able to quickly distinguish different files in project can be a great time saver!


There are large number of extensions are available go and checkout. And let me know if you find something useful, I will update list.


This library is a curated collection of sources of information related to web development, JavaScript and similar resources, selected by educator, experts, learners and made accessible to programmer community for reference.
Simply fork and star this repo:
https://github.com/roshangrewal/programming-library

Open for contributor, Anyone who find something good and want to contribute can make pull request to above repo.

technology updates today

1. Introduction:

The purpose of this Capstone Project is to help people in exploring better facilities around their neighborhood. It will help people making smart and efficient decision on selecting great neighborhood out of numbers of other neighborhoods in Scarborough, Toranto.

Lots of people are migrating to various states of Canada and needed lots of research for good housing prices and reputated schools for their children. This project is for those people who are looking for better neighborhoods. For ease of accessing to Cafe, School, Super market, medical shops, grocery shops, mall, theatre, hospital, like minded people, etc.

This Capstone Project aim to create an analysis of features for a people migrating to Scarborough to search a best neighborhood as a comparative analysis between neighborhoods. The features include median housing price and better school according to ratings, crime rates of that particular area, road connectivity, weather conditions, good management for emergency, water resources both freash and waste water and excrement conveyed in sewers and recreational facilities.

It will help people to get awareness of the area and neighborhood before moving to a new city, state, country or place for their work or to start a new fresh life.

2. Data Section

Data Link: https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M

Will use Scarborough dataset which we scrapped from wikipedia on Week 3. Dataset consisting of latitude and longitude, zip codes.

Foursquare API Data:

We will need data about different venues in different neighborhoods of that specific borough.
In order to gain that information we will use “Foursquare” locational information. Foursquare is a location data provider with information about all manner of venues and events within an area of interest. Such information includes venue names, locations, menus and even photos. As such, the foursquare location platform will be used as the sole data source since all the stated required information can be obtained through the API.

After finding the list of neighborhoods, we then connect to the Foursquare API to gather information about venues inside each and every neighborhood. For each neighborhood, we have chosen the radius to be 100 meter.

The data retrieved from Foursquare contained information of venues within a specified distance of the longitude and latitude of the postcodes. The information obtained per venue as follows:

1. Neighborhood
2. Neighborhood Latitude
3. Neighborhood Longitude
4. Venue
5. Name of the venue e.g. the name of a store or restaurant
6. Venue Latitude
7. Venue Longitude
8. Venue Category

Map of Scarborough

3. Methodology Section

Clustering Approach:

To compare the similarities of two cities, we decided to explore neighborhoods, segment them, and group them into clusters to find similar neighborhoods in a big city like New York and Toronto. To be able to do that, we need to cluster data which is a form of unsupervised machine learning: k-means clustering algorithm.

Using K-Means Clustering Approach | Most Common Venue

Most Common Venues near Neighborhood | Using Clustering

Work Flow:

Using credentials of Foursquare API features of near-by places of the neighborhoods would be mined. Due to http request limitations the number of places per neighborhood parameter would reasonably be set to 100 and the radius parameter would be set to 500.

would be set to 500.

4. Results Section

Map of Clusters in Scarborough

Average Housing Price by Clusters in Scarborough

School Ratings by Clusters in Scarborough

The Location:

Scarborough is a popular destination for new immigrants in Canada to reside. As a result, it is one of the most diverse and multicultural areas in the Greater Toronto Area, being home to various religious groups and places of worship. Although immigration has become a hot topic over the past few years with more governments seeking more restrictions on immigrants and refugees, the general trend of immigration into Canada has been one of on the rise.

Foursquare API:

This Capstone project have used Four-square API as its prime data gathering source as it has a database of millions of places, especially their places API which provides the ability to perform location search, location sharing and details about a business.

5. Discussion Section

Problem Which Tried to Solve:

The major purpose of this project, is to suggest a better neighborhood in a new city for the person who are shiffting there. Social presence in society in terms of like minded people. Connectivity to the airport, bus stand, city center, markets and other daily needs things nearby.

  • Sorted list of house in terms of housing prices in a ascending or descending order
  • Sorted list of schools in terms of location, fees, rating and reviews

6. Conclusion Section

In this Capstone project, using k-means cluster algorithm I separated the neighborhood into 10(Ten) different clusters and for 103 different lattitude and logitude from dataset, which have very-similar neighborhoods around them. Using the charts above results presented to a particular neighborhood based on average house prices and school rating have been made.

I feel rewarded with the efforts and believe this course with all the topics covered is well worthy of appreciation.
This project has shown me a practical application to resolve a real situation that has impacting personal and financial impact using Data Science tools.
The mapping with Folium is a very powerful technique to consolidate information and make the analysis and decision better with confidence.

Future Works:

This Capstone project can be continued for making it more precise in terms to find best house in Scarborough. Best means on the basis of all required things(daily needs or things we need to live a better life) around and also in terms of cost effective.

Libraries Which are Used to Develope the Project:

Pandas: For creating and manipulating dataframes.

Folium: Python visualization library would be used to visualize the neighborhoods cluster distribution of using interactive leaflet map.

Scikit Learn: For importing k-means clustering.

JSON: Library to handle JSON files.

XML: To separate data from presentation and XML stores data in plain text format.

Geocoder: To retrieve Location Data.

Beautiful Soup and Requests: To scrap and library to handle http requests.

Matplotlib: Python Plotting Module.

GitHub Link of Complete Project : https://github.com/roshangrewal/Coursera_Capstone

technical course


AI for everyone is a technical course taking which you will have greater knowledge than most CEO’s in the world. At least this is what Andrew Ng claims. So let’s find out in short what he wants to convey.

AI to create 13 Trillion Value by 2030 mostly to be used in Retail followed by Travel and Automotive sector.

AI is broadly categorized into ANI (Artificial Narrow Intelligence) and AGI(Artificial General Intelligence). With a lot of progress in ANI people falsely started believing that they are progressing in AGI.


Don’t spend much on the IT infrastructure to collect data. Feed data as early as possible to AI team so that they can figure out whether that collected data is useful and can change the Data collection strategy. Also it is not so that more the data, more the value!

Machine Learning is all about learning A to B mapping where A is the input and B is the output label whereas Data Science is more about extracting insights and conclusions from data . The output in case of Machine Learning is software whereas in case of Data Science is a slide deck.

Deep Learning is a branding name for ‘Neural Networks’ that are nothing but big Mathematical equations. Neural Networks were inspired by brain but the internal functioning is almost unrelated to how actual brain works.

Just as:
Shopping mall + Internet != Internet company
Similarly:
Any company + Deep learning != AI company.

Any problem what a human can do with 1 second of thought and for which lots of labelled data is available can be automated with supervised ML. For example- if a user will click on add or not.

AI cannot empathize or understand gestures at the moment. AI cannot learn complex task with small amounts of data.

For Machine Learning:
Collect Data, Train Model and Deploy model. 
For Data Science:
Collect Data, Analyze Data, Suggest Changes.
For example: In recruitment, Data Science will help us to optimize the recruiting process by analyzing data. Whereas machine Learning can help in automated resume screening.

Select Projects that are feasible and both valuable for your business. While deciding a project both AI experts and Domain Experts should work together.

Automate tasks not jobs. Understand Pain Points in your business.

You can make progress even without big data.

In addition to Business Diligence and Technical Diligence, think of Ethical diligence as well whether the project you are building will bring some good to Humans.

To the AI team, specify your statistical acceptance criteria on the test set.

Roles:
Software Engineer: write software code like a function/subroutine.
Machine Learning Engineer: Responsible for creating models
Machine Learning Scientist: Responsible for extending state of the art
Applied ML Scientist: A role in between ML Engineer and Researcher
Data Scientist: Examine Data and provide insights to drive business decisions
Data Engineer: Make sure data is easily accessible in a secure and cost effective way
AI Product Manager: What to build, whats valuable and feasible

Executing Relevant Pilot AI projects can set the traction for 6–12 months.

Create one central AI team and disperse it to multiple Business Units under the leadership of CAIO (Chief AI Officer). Initially the CEO should provide the funding to AI unit rather than a BU providing the funding and after the initial investment AI team has to show its value that is creating for the BU.

Business Leaders must understand what AI can do for their enterprise. AI Team leads should set project direction and monitor resources. In house AI engineers should be trained to work on AI pipeline.

CLO should know how to curate content rather than create content.

Build an AI strategy only after executing one or two projects or it will come up as an academic strategy not practical strategy. Different companies have different strategies.

A good product started with less data will have users. Over the time these users will generate data which can be used to improve the product and so on.

Strategic Data Acquisition. Don’t monetize product for collecting useful data. New roles like Machine Learning Engineer should be promoted.

Pair Engineering Talent with Business/Sales Talent to find feasible and valuable projects

Don’t expect AI project to work the first time and don’t enforce traditional planning processes in an AI project.

Get friends to learn AI, brainstorm projects and find a mentor.

Neither be too optimistic about AI that superintelligence is coming. Neither be too pessimistic about AI that AI winter is coming ! Be somewhere in middle!

Explain-ability of AI is hard.

AI can become biased with biased data.

AI systems are open to Adversarial Attacks. In future companies might be at war with the adversarial attackers.

US and China are leading in AI but this technology is still immature giving other nations an equal advantage to compete.

By 2030 according to a report by McKinsey & Company
Jobs displaced by AI: 400–800 Million
Jobs created by AI: 555–890 Million

Thank you Andrew Ng! For such an amazing course & content I’ve ever learned.

#Machine #Learning #Artificial #Intelligence #Data #Science #Deep #Learning

artificial intelligence
  1. What is Artificial Intelligence?
    Artificial Intelligence is an area of computer science that emphasizes the creation of intelligent machine that work and reacts like humans.


2) What is an artificial intelligence Neural Networks?
Artificial intelligence Neural Networks can model mathematically the way biological brain works, allowing the machine to think and learn the same way the humans do- making them capable of recognizing things like speech, objects and animals like we do.


3) What are the various areas where AI (Artificial Intelligence) can be used?
Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics’s, etc.


4) Which is not commonly used programming language for AI?
Perl language is not commonly used programming language for AI.


5) What is Prolog in AI?
In AI, Prolog is a programming language based on logic.


6) Give an explanation on the difference between strong AI and weak AI?
Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools.


7) Mention the difference between statistical AI and Classical AI?
Statistical AI is more concerned with “inductive” thought like given a set of pattern, induce the trend etc. While, classical AI, on the other hand, is more concerned with “ deductive” thought given as a set of constraints, deduce a conclusion etc.


8) What is alternate, artificial, compound and natural key?
Alternate Key: Excluding primary keys all candidate keys are known as Alternate Keys.
Artificial Key: If no obvious key either stands alone or compound is available, then the last resort is to, simply create a key, by assigning a number to each record or occurrence. This is known as artificial key.
Compound Key: When there is no single data element that uniquely defines the occurrence within a construct, then integrating multiple elements to create a unique identifier for the construct is known as Compound Key.
Natural Key: Natural key is one of the data element that is stored within a construct, and which is utilized as the primary key.


9) What does a production rule consist of?
The production rule comprises of a set of rule and a sequence of steps.


10) Which search method takes less memory?
The “depth first search” method takes less memory.


11) Which is the best way to go for Game playing problem?
Heuristic approach is the best way to go for game playing problem, as it will use the technique based on intelligent guesswork. For example, Chess between humans and computers as it will use brute force computation, looking at hundreds of thousands of positions.


12) A* algorithm is based on which search method?

A* algorithm is based on best first search method, as it gives an idea of optimization and quick choose of path, and all characteristics lie in A* algorithm.


13) What does a hybrid Bayesian network contain?
A hybrid Bayesian network contains both a discrete and continuous variables.


14) What is agent in artificial intelligence?
Anything perceives its environment by sensors and acts upon an environment by effectors are known as Agent. Agent includes Robots, Programs, and Humans etc.


15) What does Partial order or planning involve?
In partial order planning , rather than searching over possible situation it involves searching over the space of possible plans. The idea is to construct a plan piece by piece.


16) What are the two different kinds of steps that we can take in constructing a plan?
a) Add an operator (action)
b) Add an ordering constraint between operators


17) Which property is considered as not a desirable property of a logical rule-based
system?

“Attachment” is considered as not a desirable property of a logical rule based system.


18) What is Neural Network in Artificial Intelligence?
In artificial intelligence, neural network is an emulation of a biological neural system, which receives the data, process the data and gives the output based on the algorithm and empirical data.


19) When an algorithm is considered completed?
An algorithm is said completed when it terminates with a solution when one exists.


20) What is a heuristic function?
A heuristic function ranks alternatives, in search algorithms, at each branching step based on the available information to decide which branch to follow.


21) What is the function of the third component of the planning system?
In a planning system, the function of the third component is to detect when a solution to problem has been found.


22) What is “Generality” in AI ?
Generality is the measure of ease with which the method can be adapted to different domains of application.


23) What is a top-down parser?
A top-down parser begins by hypothesizing a sentence and successively predicting lower level constituents until individual pre-terminal symbols are written.


24) Mention the difference between breadth-first search and best first search in artificial intelligence?
These are the two strategies which are quite similar. In best first search, we expand the nodes in accordance with the evaluation function. While, in breadth first search a node is expanded in accordance to the cost function of the parent node.


25) What are frames and scripts in “Artificial Intelligence”?
Frames are a variant of semantic networks which is one of the popular ways of presenting nonprocedural knowledge in an expert system. A frame which is an artificial data structure is used to divide knowledge into substructure by representing “stereotyped situations’. Scripts are similar to frames, except the values that fill the slots must be ordered. Scripts are used in natural language understanding systems to organize a knowledge base in terms of the situation that the system should understand.


26) What is FOPL stands for and explain its role in Artificial Intelligence?
FOPL stands for First Order Predicate Logic, Predicate Logic provides
a) A language to express assertions about certain “World”
b) An inference system to deductive apparatus whereby we may draw conclusions from such assertion
c) A semantic based on set theory


27) What does the language of FOPL consists of
a) A set of constant symbols
b) A set of variables
c) A set of predicate symbols
d) A set of function symbols
e) The logical connective
f) The Universal Quantifier and Existential Qualifier
g) A special binary relation of equality


28) For online search in ‘Artificial Intelligence’ which search agent operates by
interleaving computation and action?

In online search, it will first take action and then observes the environment.


29) Which search algorithm will use a limited amount of memory in online search?
RBFE and SMA* will solve any kind of problem that A* can’t by using a limited amount of memory.


30) In ‘Artificial Intelligence’ where you can use the Bayes rule?
In Artificial Intelligence to answer the probabilistic queries conditioned on one piece of evidence, Bayes rule can be used.


31) For building a Bayes model how many terms are required?
For building a Bayes model in AI, three terms are required; they are one conditional probability and two unconditional probability.


32) While creating Bayesian Network what is the consequence between a node and its
predecessors?

While creating Bayesian Network, the consequence between a node and its predecessors is that a node can be conditionally independent of its predecessors.


33) To answer any query how the Bayesian network can be used?
If a Bayesian Network is a representative of the joint distribution, then by summing all the relevant joint entries, it can solve any query.


34) What combines inductive methods with the power of first order representations?
Inductive logic programming combines inductive methods with the power of first order representations.


35) In Inductive Logic Programming what needed to be satisfied?
The objective of an Inductive Logic Programming is to come up with a set of sentences for the hypothesis such that the entailment constraint is satisfied.


36) In top-down inductive learning methods how many literals are available? What are they?
There are three literals available in top-down inductive learning methods they are
a) Predicates
b) Equality and Inequality
c) Arithmetic Literals


37) Which algorithm inverts a complete resolution strategy?
‘Inverse Resolution’ inverts a complete resolution, as it is a complete algorithm for learning first order theories.


38) In speech recognition what kind of signal is used?
In speech recognition, Acoustic signal is used to identify a sequence of words.


39) In speech recognition which model gives the probability of each word following each word?
Biagram model gives the probability of each word following each other word in speech recognition.


40) Which algorithm is used for solving temporal probabilistic reasoning?
To solve temporal probabilistic reasoning, HMM (Hidden Markov Model) is used, independent of transition and sensor model.


41) What is Hidden Markov Model (HMMs) is used?
Hidden Markov Models are a ubiquitous tool for modelling time series data or to model sequence behaviour. They are used in almost all current speech recognition systems.


42) In Hidden Markov Model, how does the state of the process is described?
The state of the process in HMM’s model is described by a ‘Single Discrete Random Variable’.


43) In HMM’s, what are the possible values of the variable?
‘Possible States of the World’ is the possible values of the variable in HMM’s.


44) In HMM, where does the additional variable is added?
While staying within the HMM network, the additional state variables can be added to a temporal model.


45) In Artificial Intelligence, what do semantic analyses used for?
In Artificial Intelligence, to extract the meaning from the group of sentences semantic analysis is used.


46) What is meant by compositional semantics?
The process of determining the meaning of PQ from P,Q and is known as Compositional Semantics.


47) How logical inference can be solved in Propositional Logic?
In Propositional Logic, Logical Inference algorithm can be solved by using
a) Logical Equivalence
b) Validity
c) Satisfying ability


48) Which process makes different logical expression looks identical?
‘Unification’ process makes different logical expressions identical. Lifted inferences require finding a substitute which can make a different expression looks identical. This process is called unification.


49) Which algorithm in ‘Unification and Lifting’ takes two sentences and returns a
unifier?

In ‘Unification and Lifting’ the algorithm that takes two sentences and returns a unifier is ‘Unify’ algorithm.


50) Which is the most straight forward approach for planning algorithm?
State space search is the most straight forward approach for planning algorithm because it takes account of everything for finding a solution.

#Top50 #Artificial #Intelligence #Interview #Questions #Answers

There’s no single hack for getting more work done in less time, but instead a host of habits, and work systems can produce the best return on your time.

Getting more work done is about knowing what to do, when to do it, and how to get it done in the shortest possible time to maximize the little time you have everyday.

It means means choosing tasks that strategically align with your work objectives.

It’s the ratio between input and output.

Is everything really urgent?

What are the most important actions you can take today that will get your closer to your work goals in the shortest possible time?

Imagine the repercussions of choosing to do urgent (but not important) tasks instead of focusing on important actions.

“The secret to mastering your time is to systematically focus on importance and suppress urgency.”

Oliver Emberton said that.

It’s profound and so true.

Urgency wrecks productivity.

Urgent but unimportant tasks are major distractions.

In 1954, former U.S President Dwight D. Eisenhower said,


I have two kinds of problems: the urgent and the important. The urgent are not important, and the important are never urgent.

Separating important tasks from urgent ones is a problem for many people.

The urgent are not important, and the important are never urgent.

Urgent tasks put us into constant “reply mode.”

They are distractions.

Important work are tasks we have planned that move goals.

Our brains are so drawn to urgency that we choose “objectively worse options over objectively better (important) options.

To maximise time and do more focused work, question your choices constantly, and develop the ability to watch your mind as it gets whipped up by sudden requests.

When a task you have not planned to do falls onto your plate, ask yourself:

“Is this really important?”

And then think about not only how, but when, to best handle it.


What’s on your plate?

When you try to tackle too many tasks everyday, you will be overwhelmed and achieve less.

When everything is important, you will be tempted to skillfully juggle multiple priorities at the same time, and your productivity suffers in the process.

It pays to prioritise your tasks and work on the most important ones first thing in the morning, when you are most active.


Even if everything on your plate is supposed to be equally important, you still need a way to break down which ones you spend your time on, and how you slice up your time. says Alan Henry of Lifehacker

Whenever you are faced with a lot to do, take a step back to recognise the rushed mindset and its consequences.

Instead of rushing to get them done at the same time, start by asking yourself:

“Is this really important?”

And then think about not only how, but when, to best handle it.

Ultimately, the goal should be to question your choices constantly, and to develop the ability to recognize tasks that just distract you from your real work.


Stop feeding your distractions

Interruptions like notifications, loud noises, social media, someone knocking on your door, and switching to check emails every now and then, break your flow.

They interrupt your concentration.

They’re just enough to pull your focus away and make you have to start over.

Anytime you are pulled away from your tasks, it takes time to readjust to them when you jump back in — up to 25 minutes in many cases.

Your life keeps diminishing while you waste your time feeding your distractions.

Successful people priorities! They focus! They disconnect from everything else to get tasks done.

Beware of deceptive time-wasting activities that disguise themselves as work; Lengthy discussions with colleagues, long meetings and treating other people’s work as “emergencies” when you should be concentrating on your high-value work.

Writing in the first century, Seneca was surprised by how little people seemed to value their lives as they were living them — how busy, terribly busy, everyone seemed to be, and wasteful of their time.

He noticed how even wealthy people hustled their lives along, ruing their fortune, anticipating a time in the future when they would rest.


In his book (translated by John W. Basore), “On the Shortness of Life ,”  Seneca  offers powerful insights into the art of living. He observed, “It is not that we have so little time but that we lose so much. … The life we receive is not short but we make it so; we are not ill provided but use what we have wastefully.”

“Life is long if you know how to use it,” he counselled.

Take control of your time and start distributing it right.

Start by reviewing your daily routine.

Track your daily activities for some time to clearly see where your time is being spent. Meetings, phone calls, emails, notifications, small chats, and many other distractions are constantly splitting your attention.

Record ALL your appointments, deadlines, and everything in-between.Analyse the actual time you spend on each activity with what you think is the best amount for each.


Schedule the heck out of your days. Schedule everything in advance.

Make a plan and know what’s going on each day.

This helps you figure out how you’re spending your time

Notice where time leaks, then declutter your routine.


Stop doing busywork

Busy does not necessarily means productive.

Busy work makes you feel like you are moving quickly and being productive in the process. But in effect, you are not.

If you took time to measure your work, you will be surprised at how little valuable work you are doing.

Oliver Burkeman of BBC writes, “When you’re busy, you’re more likely to make poor time-management choices — taking on commitments you can’t handle, or prioritizing trifling tasks over crucial ones. A vicious spiral kicks in: your feelings of busyness leave you even busier than before.”


Many of us confuse being “busy” with being effective, or efficient.

If you start your day by answering emails. You could get sucked into answering questions, replying to every email, and advancing the cause of other people’s actions.

Be proactive about your emails.

Don’t get caught up in reactive mode.

“Most of us have no problem with being busy, but we’re often busy on the wrong things,” says Angie Morgan, co-author of Spark: How to Lead Yourself and Others to Greater Success. “You could spend nine to five just emailing, but that’s not driving results or moving you toward longer, bigger goals. When people say, ‘I’m so busy,’ it really means, ‘I’m a poor planner,’ or, ‘I don’t know how to priorities or delegate.”

Adopt the “one thing” approach.

Make the hard choices and work on your most important priorities instead of responding to urgent tasks.

Your time is limited. Doing everything is not an option.

A simple system to change how you work

Set a very clear intention of how your day will go the next morning, particularly in the beginning, the night before.

Visualizing this intention and writing it down into your schedule can make it happen more automatically in the morning without wasting time.

Planning tomorrow today is a powerful habit that changes everyday.

It’s a system that can completely changes how you work:

  1. Before the day ends, identify and write down the best actions (to-do) you need to take tomorrow that will help you get closer to your work goals.
  2. Every morning, focus on completing your action list from yesterday before midday.
  3. Rinse, improve and repeat. Every day. Every week. Every month. Every year.

You could double your efficiency with this simple process/habit.

Adopt the 1–3–5 method to create and manage your action list for the day

On any given day, assume that you can only accomplish one big thing, three medium things, and five small things, and narrow down your to-do list to those nine items.

This means that your daily schedule will feature:

1. One very important task;

2. Three tasks of medium importance

3. Five little things

Of course, this can be flexible, depending on important actions you need to take to advance your work goals.

A daily priority list gives you a great road-map to follow so that you don’t feel overwhelmed and don’t have to waste time thinking about what needs done.

I use a combination of these methods to get through the day depending on how much work I have to get through.

As you practice being ruthless with your to-do, you’ll find it gets easier and you’ll be able to pick the right method at the right time.

#Productivity #Work #Creativity #SelfImprovement #PersonalDevelopment #Life #Hacks