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Showing posts with the label Self learning

Notes and learnings from Kaggle (Intro to Programming)

 Intro to programming Arithmetic and Variables Shift + Enter to run a code removing # sign is called uncommenting print("Hello, world") print(1+2) print(3**2) print(((1 + 3) * (9 - 2) / 2) ** 2) #Multiply 3 by 2 print(3*2) Multiply 3 by 2 #create test_var and give value test_var = 4+5 #print the value print(test_var) # set the value 3  my_var = 3 #print the value my_var print(my_var) #Set the new value 100 my_var = 100 #print the new my_var print(my_var) print(my_var) print(test_var) my_var = my_var + 3 #Increase value by 3 my_var = my_var + 3 #print the increased value print(my_var) num_years = 4 days_per_year = 365 hours_per_day = 24 seconds_per_hour = 60 secs_per_year = 60 #Calculate umber of seconds of 4 year total_secs = secs_per_year * seconds_per_hour * hours_per_day * days_per_year * num_years #print result print(total_secs) num_years = 4 days_per_year = 365 hours_per_day = 24 seconds_per_hour = 60 secs_per_year = 60 #update the days per year days_per_year = 365.25 #C

Learn Basics of Data Science with Kaggle

Kaggle is a branch of Google LLC which is an online community of data scientists and machine learning practitioners. It first launched in 2010; and Google’s announcement of acquiring Kaggle came on 8 March 2017. It permits the user to work and experiment in the community with various types of data. There are competitions and challenges to attend and practice. At the time of the information age, it is important to know about data and its usage. Data is being used everywhere and the changing role in many of our careers requires knowledge of code, data, machine learning and what not! In this time, investing in you can be beneficial and there is always a need to develop your skills with time. Kaggle has a free learning module where you can learn about different aspects of data science with which you can do independent data science projects. Kaggle has divided the topics narrowly so that the learner can easily learn with no time and to the specific topic. Moreover, the learner will get

How to identify fake/ predatory/ cloned journals in academics

“Writing Impactful Research (WIR)” programme conducted by the Sabaragamuwa University of Sri Lanka in association with Emerald Publishing and Gulf Medical University from 22nd April 2021 to 05th August 2021 through GoToWebinar Platform. Resource Person of s ession 16 was   Dr. Sumit Narula. He is the Deputy Dean Research (Publication and Citations) at the Amity University, India has given fifteen Crucial Point Checklists on 05 August 2021 session. Most Fake/Predatory/Cloned journals will not have any submission deadline. They will always charge money and will give you early publications. Most of them will be having multiple journals doing the same job. They also use the cloned websites with same logo and ISSN number. They have fake stamps of SCOPUS or Web of Science. Google indexing is very easy and there is no science involved in it and it is not useful anywhere in academics, but it gives you more citations. Always see the UGC CARE List and SCOPUS DATA before submitting to any journal