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Import Data

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  • Import Data youtube.com channel data-science video youtube 2020-07-31 12:00
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    I am an introvert. I gain energy from spending more time by myself. Due to my introverted nature, I'm not very talkative so making YouTube videos was awful in the beginning. In this video, I talk about why I decided to start a YouTube channel as an introvert. Connect with...

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    I am an introvert. I gain energy from spending more time by myself. Due to my introverted nature, I'm not very talkative so making YouTube videos was awful in the beginning. In this video, I talk about why I decided to start a YouTube channel as an introvert. Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata 🔗 Kaggle: https://www.kaggle.com/importdata #ImportData #DataScience #YouTubeForIntroverts
  • Import Data youtube.com channel data-science video youtube 2020-07-28 05:10
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  • Import Data youtube.com channel data-science video youtube 2020-07-25 11:30
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    As I am about to start a new chapter in my life very soon, I wanted to talk about the plans I made for my YouTube channel. In two weeks, I am starting my very first full-time position and I am very excited about it. I am going to prioritize my job first, but that doesn't mean...

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    As I am about to start a new chapter in my life very soon, I wanted to talk about the plans I made for my YouTube channel. In two weeks, I am starting my very first full-time position and I am very excited about it. I am going to prioritize my job first, but that doesn't mean I won't be producing content on YouTube. YouTube has given me so many valuable things and I'd love to continue this journey with you guys. Here are the future plans: ✅Machine Learning Mondays ✅Tableau Tuesdays ✅Python Thursdays/R Thursdays ✅SQL Saturdays ✅Vlog and talking videos Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata 🔗 Kaggle: https://www.kaggle.com/importdata #ImportData #DataScience #YouTube
  • Import Data youtube.com channel data-science video youtube 2020-07-15 11:30
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    In this video, I demonstrate how to use Python's replace method to replace string values in text files and in data frames. In data science projects, you often need to do data cleaning and data preprocessing associated with string values. The replace method can come in handy...

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    In this video, I demonstrate how to use Python's replace method to replace string values in text files and in data frames. In data science projects, you often need to do data cleaning and data preprocessing associated with string values. The replace method can come in handy when you need to do those tasks. 👨‍💻 My GitHub Link: https://github.com/importdata/Python/blob/master/String_Replacement_in_Python.ipynb 🎥 Python Playlist: https://www.youtube.com/watch?v=fptTG4OF4f4&list=PLfwO4-8NiQkE2wm7WkPKXqoIuXqJZJ377 Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DataScience #Python
  • Import Data youtube.com channel data-science video youtube 2020-07-13 11:30
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    In this video, I give a simple explanation of the decision tree classifier and I demonstrate how to classify the English Premier League clubs (Top 4, Mid 4, and Bottom 4) in FIFA 20 using decision tree. The goal is to create a model that predicts the value of a target...

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    In this video, I give a simple explanation of the decision tree classifier and I demonstrate how to classify the English Premier League clubs (Top 4, Mid 4, and Bottom 4) in FIFA 20 using decision tree. The goal is to create a model that predicts the value of a target variable by learning simple decision rules based on the predictors. Decision trees use criteria such as information gain (IG), entropy, and Gini. Decision tree is simple to understand and is easy to interpret with the tree-like plot. It only requires little data preparation and it can handle multi-class problems well. However, it can create over-complex trees that do not generalize the data well (aka. overfitting). You can avoid overfitting by pruning the tree and setting optimal parameters. 👨‍💻 My GitHub Repo: https://github.com/importdata/Classification-in-FIFA-20 🎥 Classification Tutorials: https://www.youtube.com/watch?v=Arc80xcrPE8&list=PLfwO4-8NiQkHLS9c2LllFonvYrQwwwZEq 🔗 Kaggle's FIFA 20 Dataset Link: https://www.kaggle.com/stefanoleone992/fifa-20-complete-player-dataset/data?select=players_20.csv Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DataScience #DecisionTree
  • Import Data youtube.com channel data-science video youtube 2020-07-10 11:30
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    GitHub recently had a huge update and they added a hidden feature that lets you customize your GitHub profile page. I personally think this is a cool feature as your profile page will look more appealing! ✔️ Steps 1. Go to your GitHub page 2. Create a new repository 3. Name...

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    GitHub recently had a huge update and they added a hidden feature that lets you customize your GitHub profile page. I personally think this is a cool feature as your profile page will look more appealing! ✔️ Steps 1. Go to your GitHub page 2. Create a new repository 3. Name your repository with your username to unlock the hidden feature 4. Initialize a READ.me file 5. Play with Markdown and customize to your own preference 6. Enjoy your awesome-looking profile page! 👨‍💻 My GitHub Repo: https://github.com/importdata/importdata 🔗 Markdown Cheat Sheet: https://www.markdownguide.org/cheat-sheet/ 🔗 Cloudinary Link: https://cloudinary.com/ Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DataScience #GitHub
  • Import Data youtube.com channel data-science video youtube 2020-07-08 11:30
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    In this video, I give a simple explanation of logistic regression and I demonstrate how to classify the English Premier League clubs (Top 4, Mid 4, and Bottom 4) in FIFA 20 using logistic regression. Although there's a term "regression" in its name, logistic regression is...

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    In this video, I give a simple explanation of logistic regression and I demonstrate how to classify the English Premier League clubs (Top 4, Mid 4, and Bottom 4) in FIFA 20 using logistic regression. Although there's a term "regression" in its name, logistic regression is widely used for classification. It fits an S-shaped plot (aka. Sigmoid function) to find the probability. Logistic regression works well with both quantitative and qualitative predictors. Also, it doesn’t have any distribution assumptions for predictors. 👨‍💻 My GitHub Repo: https://github.com/importdata/Classification-in-FIFA-20 🎥 Classification Tutorials: https://www.youtube.com/watch?v=Arc80xcrPE8&list=PLfwO4-8NiQkHLS9c2LllFonvYrQwwwZEq 🔗 Kaggle's FIFA 20 Dataset Link: https://www.kaggle.com/stefanoleone992/fifa-20-complete-player-dataset/data?select=players_20.csv Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DataScience #LogisticRegression
  • Import Data youtube.com channel data-science video youtube 2020-07-02 11:30
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    In this video, I give a simple explanation of the K-Nearest Neighbors (KNN) classifier and I classify the English Premier League clubs (Top 4, Mid 4, and Bottom 4) in FIFA 20 using KNN. KNN is a non-parametric algorithm which means that it doesn't make any distribution...

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    In this video, I give a simple explanation of the K-Nearest Neighbors (KNN) classifier and I classify the English Premier League clubs (Top 4, Mid 4, and Bottom 4) in FIFA 20 using KNN. KNN is a non-parametric algorithm which means that it doesn't make any distribution assumptions. So, it's useful when you don't know the distribution of the dataset. 👨‍💻 My GitHub Repo: https://github.com/importdata/Classification-in-FIFA-20 🔗 Kaggle's FIFA 20 Dataset Link: https://www.kaggle.com/stefanoleone992/fifa-20-complete-player-dataset/data?select=players_20.csv Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #KNN #PremiereLeague
  • Import Data youtube.com channel data-science video youtube 2020-06-29 21:04
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    This is part 3 of the clustering algorithm series. In this tutorial, I demonstrate how to group FIFA 20 players with similar skillsets using the DBSCAN algorithm. DBSCAN is an abbreviation of Density-Based Spatial Clustering of Applications with Noise. It is known to be...

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    This is part 3 of the clustering algorithm series. In this tutorial, I demonstrate how to group FIFA 20 players with similar skillsets using the DBSCAN algorithm. DBSCAN is an abbreviation of Density-Based Spatial Clustering of Applications with Noise. It is known to be robust with detecting outliers (Anomaly Detection). However, the outcome varies depending on the values of epsilon and the minimum points. DBSCAN won't work well with a sparse dataset as well. 👨‍💻 My GitHub Repo: https://github.com/importdata/Clustering-FIFA-20-Players 🎥 Clustering Algorithms Playlist: https://www.youtube.com/watch?v=ENWhKh8RkaU&list=PLfwO4-8NiQkF0tXQYfKwwvITakjHQPFHp Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DBSCAN #FIFA20
  • Import Data youtube.com channel data-science video youtube 2020-06-22 21:48
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    In this video, I demonstrate how to convert the R codes into reports. It's easy to turn Python codes into reports using Jupyter Notebook and Google Colab. You can also do the same for R codes as well! You need to install R (the actual language) and R Studio (the IDE) to make...

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    In this video, I demonstrate how to convert the R codes into reports. It's easy to turn Python codes into reports using Jupyter Notebook and Google Colab. You can also do the same for R codes as well! You need to install R (the actual language) and R Studio (the IDE) to make it work. Then you use R Markdown to write your code and report. Once you are done, you can output your work to HTML, PDF, and MS Word. 🔗 R Installation Link: https://cran.r-project.org/bin/windows/base/ 🔗 R Studio Installation Link: https://rstudio.com/products/rstudio/download/ ⏰ 0:53 Installing R 1:49 Installing R Studio 2:25 Downloading the KnitR Package in R Studio 3:00 Using R Markdown to write code and report 3:34 Understanding how to use R Markdown 4:28 Converting R code into a report (HTML, PDF, MS Word) 📝 My Medium article: https://towardsdatascience.com/creating-reports-with-r-markdown-c6031ecdd65c?source=friends_link&sk=9be12df30587896efda4841814a9bcac Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #RMarkdown #RStudio
  • Import Data youtube.com channel data-science video youtube 2020-06-19 21:37
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    This is part 2 of the clustering algorithm series. In this tutorial, I demonstrate how to group FIFA 20 players with similar skillsets using hierarchical clustering algorithms. Hierarchical clusterings' results are summarized in a dendrogram – a tree-like plot. I particularly...

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    This is part 2 of the clustering algorithm series. In this tutorial, I demonstrate how to group FIFA 20 players with similar skillsets using hierarchical clustering algorithms. Hierarchical clusterings' results are summarized in a dendrogram – a tree-like plot. I particularly use single linkage, average linkage, centroid linkage, and complete linkage in this tutorial. 🎥 Clustering Algorithms Playlist: https://www.youtube.com/watch?v=wjlNySHpK9w&list=PLfwO4-8NiQkF0tXQYfKwwvITakjHQPFHp 👨‍💻 My GitHub Repo: https://github.com/importdata/Clustering-FIFA-20-Players 📝 My Medium article: https://towardsdatascience.com/grouping-soccer-players-with-similar-skillsets-in-fifa-20-part-2-hierarchical-clustering-839705f6d37d?source=friends_link&sk=f3a4d1db45e35b717febcb79fd986e36 Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #HierarchicalClustering #FIFA20
  • Import Data youtube.com channel data-science video youtube 2020-06-18 03:39
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    This is part 1 of the clustering algorithm tutorials in machine learning. Soccer (European Football) has been one of my favorite sports ever since I was little. I used to bring a ball with me anywhere I went so that I could maximize my opportunity to play soccer. In this...

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    This is part 1 of the clustering algorithm tutorials in machine learning. Soccer (European Football) has been one of my favorite sports ever since I was little. I used to bring a ball with me anywhere I went so that I could maximize my opportunity to play soccer. In this tutorial, I use the K-Means clustering algorithm to group soccer players in FIFA 20 with similar skillsets (by positions). 👨‍💻 My GitHub Repo: https://github.com/importdata/Clustering-FIFA-20-Players 📝 My Medium article:https://towardsdatascience.com/grouping-soccer-players-with-similar-skillsets-in-fifa-20-part-1-k-means-clustering-c4a845db78bc?source=friends_link&sk=8057976968214fd464a3e8ada31c62b3 🔗 Kaggle's FIFA 20 Dataset Link: https://www.kaggle.com/stefanoleone992/fifa-20-complete-player-dataset/data?select=players_20.csv Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #KMeansClustering #FIFA20
  • Import Data youtube.com channel data-science video youtube 2020-06-16 00:45
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    In this video, I share my story on why I (a South Korean) decided to study abroad in the U.S. I was born and raised in South Korea and I came to the U.S. in 2011. I have been living here for about 7 years (excluding 2 years of the mandatory military service in Korea). The...

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    In this video, I share my story on why I (a South Korean) decided to study abroad in the U.S. I was born and raised in South Korea and I came to the U.S. in 2011. I have been living here for about 7 years (excluding 2 years of the mandatory military service in Korea). The transition was definitely not easy. I never had to speak English in my daily life in Korea and all of a sudden, I was thrown into an English speaking country. The food and culture are different, so I definitely went through culture shock. I hope this video can motivate students who are considering studying abroad. ⏰ 0:08 Intro Why did I decide to study abroad in the U.S.? 1:20 My drive to learn English 2:03 Education and career opportunities 2:55 Cultural dynamics 3:27 Final remarks 📝 My Medium article: https://medium.com/@importdata/6000-miles-10-000-km-away-from-my-home-country-b457e5ee8e77?sk=e676dce7b2afa1bf671ba19532d1f19b Connect with Import Data on these platforms 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #USInternationalStudent #InternationalStudents
  • Import Data youtube.com channel data-science video youtube 2020-06-13 02:16
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    This is the last part of the tutorial where I show how to document your work on GitHub and how to host a simple portfolio website using GitHub pages. I personally enjoyed this journey as I learned technologies that I haven't used before. I learned how to use GridSearchCV to...

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    This is the last part of the tutorial where I show how to document your work on GitHub and how to host a simple portfolio website using GitHub pages. I personally enjoyed this journey as I learned technologies that I haven't used before. I learned how to use GridSearchCV to find optimal parameters and I learned how to deploy a model and create a web app. 🌐 Finished Simple Portfolio Website https://importdata.github.io/ds-simple-portfolio/ 👨‍💻 My GitHub Repo: https://github.com/importdata/kpop-analysis 🎥 Machine Learning Tutorials: https://www.youtube.com/watch?v=DgTG2Qg-x0k&list=PLfwO4-8NiQkFVYIV8cIUjCQA6yTbvV2L_&index=1 Other Links from Import Data 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DataSciencePortfolio #GitHub
  • Import Data youtube.com channel data-science video youtube 2020-06-10 00:37
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    This is part 4 of the series where I talk about interview preparation for entry-level data science roles and the mindset you should have. In this video, I talk about the followings: - How to prepare for entry-level data science technical interviews - How to prepare for...

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    This is part 4 of the series where I talk about interview preparation for entry-level data science roles and the mindset you should have. In this video, I talk about the followings: - How to prepare for entry-level data science technical interviews - How to prepare for behavioral interviews - The mindset you should have before going into interviews - Some other useful tips ⏰ 0:24 Intro Technical Interview Tips 1:03 Tip 1 - Do as many projects as you can (SQL, Python/R) 1:22 Tip 2 - Be prepared for basic machine learning questions 1:49 Tip 3 - Know your resume Behavioral Interview Tips 2:15 Tip 1 - Research the company 2:28 Tip 2 - Use Glassdoor’s interview questions 2:39 Tip 3 - Be yourself and show your character 2:57 The mindset you should have before interviews Other tips 4:06 Practice interviews - mock interviews or ask friends or family for help 4:18 Try doing projects on the specific area of the company. 4:34 Be honest 4:48 Ask Questions 5:02 Make sure to write a thank-you email within 24 hours after the interview 📝 My Medium article: https://towardsdatascience.com/how-i-landed-a-job-in-data-science-without-a-masters-or-ph-d-part-4-interview-ad9edc24f93d?source=friends_link&sk=1c73e7830a6d6013c5480cc7c67b1487 🔗 Links to Machine Learning Interview Questions https://www.springboard.com/blog/machine-learning-interview-questions/ https://www.analyticsvidhya.com/blog/2016/09/40-interview-questions-asked-at-startups-in-machine-learning-data-science/ https://elitedatascience.com/machine-learning-interview-questions-answers Other Links from Import Data 🔗 Medium: https://medium.com/@importdata 🔗 Twitter: https://twitter.com/ImportData1 🔗 LinkedIn: https://www.linkedin.com/in/jaemin-lee-771705151/ 🔗 GitHub: https://github.com/importdata #ImportData #DataScienceInterview #DataScienceJobs
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