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programmerslife - 104.7k posts

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  • echo "hello Ig friends !!" 👋☺️
I'm back, I had to stop using IG for two reasons:
01. Deadlines 🗓️
10. Vacations after deadlines🌴🌞
I had to focus on 01 so I had to starve my distractions and I had to enjoy 10 without using the mobile because I wanted to genuinely enjoy every moment I was having 🕶️💙
Now, I'm back to the office and this semester I won't be teaching at university so I'm gonna have more time⌚ to work on side projects and other ideas I have (also to interact with you 😜). I took this picture doing probably the last commit of a project I have been working at office for 6 monthts. Now, we are doing the spring plans for the next one. I'm gonna use Sails! :3

Have a good start of the week 🤓

#programming #programmers #programmer #code #coders #programmerslife #programmerlife #girlswhocode #backend #frontend #computerscience
  • echo "hello Ig friends !!" 👋☺️
    I'm back, I had to stop using IG for two reasons:
    01. Deadlines 🗓️
    10. Vacations after deadlines🌴🌞
    I had to focus on 01 so I had to starve my distractions and I had to enjoy 10 without using the mobile because I wanted to genuinely enjoy every moment I was having 🕶️💙
    Now, I'm back to the office and this semester I won't be teaching at university so I'm gonna have more time⌚ to work on side projects and other ideas I have (also to interact with you 😜). I took this picture doing probably the last commit of a project I have been working at office for 6 monthts. Now, we are doing the spring plans for the next one. I'm gonna use Sails! :3

    Have a good start of the week 🤓

    #programming #programmers #programmer #code #coders #programmerslife #programmerlife #girlswhocode #backend #frontend #computerscience
  • 6,537 105 21 January, 2019

Latest Instagram Posts

  • We are legion 🙌🏾
  • We are legion 🙌🏾
  • 1 0 1 minute ago
  • Principal component analysis explained
👇
Principal Component Analysis is the most frequently used concept in data science for dimensionality reduction, Here is visual explanation of the eigenvalues and eigenvector (first principal component) Blue dots the initial data on a 2D space Red dots: the projection of the blue dots onto lines, that are centered at the mean. Notice how the red dots are spread out on the rotating line in different ways depending on the position of the line (vector) on some Iines the red dots have great dispersion compared to other positions of the line. First Principal Component Eigenvectors That particular position of the rotating line (-vector)-shown in purple-where the red dots (projection of the origînal blue data) have the biggest spread out than any other line i.e, have the greatest variance on the rotating line. Eigenvalue: the actual variance of the red dots on that line. Let's say the eigenvalue (explained variance_ in sklearn) is 80 % . It means that if you project all your data to that line , you will be able to reconstruct the points with 80 % of accuracy with using only one dimension.
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Credit:Bit.ly/2nd1XeP
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Follow us on @smart.ai_
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#machinelearning#ml #deeplearning  #cs #it #python #R #iot #mit #blockchain #boats #robots #programming #coding #programmers #tech #technology #bigdata #data #innovation
#techstartup
#engineering
#developer 
#programmerslife #datascience #coder  #artificialintelligence #ai
  • Principal component analysis explained
    👇
    Principal Component Analysis is the most frequently used concept in data science for dimensionality reduction, Here is visual explanation of the eigenvalues and eigenvector (first principal component) Blue dots the initial data on a 2D space Red dots: the projection of the blue dots onto lines, that are centered at the mean. Notice how the red dots are spread out on the rotating line in different ways depending on the position of the line (vector) on some Iines the red dots have great dispersion compared to other positions of the line. First Principal Component Eigenvectors That particular position of the rotating line (-vector)-shown in purple-where the red dots (projection of the origînal blue data) have the biggest spread out than any other line i.e, have the greatest variance on the rotating line. Eigenvalue: the actual variance of the red dots on that line. Let's say the eigenvalue (explained variance_ in sklearn) is 80 % . It means that if you project all your data to that line , you will be able to reconstruct the points with 80 % of accuracy with using only one dimension.
    .
    .
    .
    Credit:Bit.ly/2nd1XeP
    .
    .
    .
    Follow us on @smart.ai_
    .
    .
    .
    #machinelearning #ml #deeplearning #cs #it #python #R #iot #mit #blockchain #boats #robots #programming #coding #programmers #tech #technology #bigdata #data #innovation
    #techstartup
    #engineering
    #developer
    #programmerslife #datascience #coder #artificialintelligence #ai
  • 35 0 28 minutes ago
  • Rate this setup 👇🤓🚀
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Photo by: @konrad.codes
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💡365 days of code? + University?💡
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Hello friends,
sorry for not posting frequently again I was thinking a lot in terms of how can I provide you the most value without actually posting useless and not meaningful content.
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I know a lot of people like pictures based on how 'cool' they look but I would like to post more frequently to provide you with interesting information about what I am working on at my university as well as what i do in my time outside university.
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My idea was to start the #365daysofcode challenge which means I will be posting once a day(I know crazy) sharing what I was working on that day + what I was doing at university.
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I’m currently doing my 2nd year Software Engineering degree so I think the information from university combined with Web Development that I do might be really meaningful for you guys.
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Honestly if you are reading this please leave your opinion below, it really helps me evaluate what you guys like and what should i talk about. (❗PLEASE COMMENT BELOW 👇🏼)
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Thank you so much 🙏🏻
Peace out! ❤
  • Rate this setup 👇🤓🚀
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    Photo by: @konrad.codes
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    .-
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    💡365 days of code? + University?💡

    Hello friends,
    sorry for not posting frequently again I was thinking a lot in terms of how can I provide you the most value without actually posting useless and not meaningful content.

    I know a lot of people like pictures based on how 'cool' they look but I would like to post more frequently to provide you with interesting information about what I am working on at my university as well as what i do in my time outside university.

    My idea was to start the #365daysofcode challenge which means I will be posting once a day(I know crazy) sharing what I was working on that day + what I was doing at university.

    I’m currently doing my 2nd year Software Engineering degree so I think the information from university combined with Web Development that I do might be really meaningful for you guys.

    Honestly if you are reading this please leave your opinion below, it really helps me evaluate what you guys like and what should i talk about. (❗PLEASE COMMENT BELOW 👇🏼)

    Thank you so much 🙏🏻
    Peace out! ❤
  • 162 4 1 hour ago