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Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
This is one of the best of investments you can make with regards to career progression and growth in technological knowledge. I was pointed in this direction by a mentor in the IT world who I highly... Read More
I came to the platform with no experience and now I am knowledgeable in Machine Learning with Python. No easy thing I must say, the sessions are challenging and go to the depths. I looked at graduate... Read More
Recruiters and HR teams in companies have a tough time scanning thousands of qualified resumes. Either they need many people to do this or they miss out on qualified candidates. This is a waste of time, money and productivity for the company.
To solve this, our resume parser application can take in millions of resumes, parse the needed fields and categorise them. This resume parser uses the popular python library - Spacy for OCR and text classifications. First we train our model with these fields, then the application can pick out the values of these fields from new resumes being input.
The dataset of resumes has the following fields:
Build a machine learning model that will predict which jobs users will apply to given their past applications, demographics and work history.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.