Test_col = len(lumns) Understanding the various features (columns) of the dataset: # Summary of numerical variables for training data setįor the non-numerical values (e.g. # Store total number of columns in testing data set # Store total number of observation in training dataset # Reading the test dataset in a dataframe using Pandas # Reading the training dataset in a dataframe using Pandas Test and train dataset.zip # Importing Libraryįrom sklearn.preprocessing import LabelEncoder Here I have provided a data set.Īs to proceed further,We need to download Test & Train data set. The purpose of this analysis is to predict the loan eligibility process. The second one we are going to see the about algorithm used to tackle our problem. The first part is going to focus on data analysis and Data visualization. We have data of some predicted loans from history. So when there is name of some ‘Data’ there is a lot interesting for ‘Data Scientists’. I have explored dataset and found a lot interesting facts about loan prediction. This is the reason why I would like to introduce you to an analysis of this one. But this has also been solved by experts we can chat with and believe me when I say this they will do whatever it takes to solve your problem even if it takes longer than expected.The dataset Loan Prediction: Machine Learning is indispensable for the beginner in Data Science, this dataset allows you to work on supervised learning, more preciously a classification problem. Another thing we all struggle with is how to really connect with someone if we're stuck somewhere because there are so many solutions. The fact that I can have a reliable route and videos explaining each tool in detail really motivated me to continue with the platform. The main issue was the right path to guide us in using these tools and adding to the resume, and that's exactly what ProjectPro got me through. One of the standout features was that it featured real projects on topics I just read about, across different job descriptions at the time. I was one of them too, and that's when I came across ProjectPro while watching one of the SQL videos on the E-Learning Bridge YouTube channel. Very few ways to do it are Google, YouTube, etc. As the cherry on the icing, there are experts to guide you with resume writing and interview preparation as well, to culminate the whole process of making you job-ready.Īs a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. They not only have enterprise-grade projects, but also set up 1:1 sessions with seasoned experts in case we get stuck, or are having trouble understanding a certain concept. I also had a conversation with their investors, and I was really glad to articulate my appreciation of the product. I have had a couple of interactions with Binny and each time I was left happy and content. I am a customer who is not only satisfied with ProjectPro but also mighty impressed by how Dezyre bends over backward to ensure customer satisfaction. I now work at a leading healthcare startup as a Senior Analytics Consultant. I managed to switch to analytics companies, only because of the relevant practical experience this product served me with. This is when I was introduced to ProjectPro, and the fact that I am on my second subscription year only goes to prove that the ROI is satisfactory. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge. I come from Northwestern University, which is ranked 9th in the US.
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