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Make great data visualizations. A great way to see the power of coding!
- Subjects:
- Computing
- Keywords:
- Information visualization Python (Computer program language)
- Resource Type:
- Others
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Learn to handle missing values, non-numeric values, data leakage and more. Your models will be more accurate and useful.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Machine learning
- Resource Type:
- Others
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Learn the most important language for data science.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
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Others
Learn SQL for working with databases, using Google BigQuery to scale to massive datasets.
- Subjects:
- Computing
- Keywords:
- Database management SQL (Computer program language)
- Resource Type:
- Others
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Distinguish yourself by learning to work with text data.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Natural language processing (Computer science)
- Resource Type:
- Others
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Others
Use TensorFlow to take machine learning to the next level. Your new skills will amaze you.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Machine learning
- Resource Type:
- Others
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Discover the most effective way to improve your models.
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Python (Computer program language)
- Resource Type:
- Others
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Solve short hands-on challenges to perfect your data manipulation skills.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Electronic data processing Information visualization
- Resource Type:
- Others
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Others
This work introduces a handwritten Manipuri Meetei-Mayek character dataset which consists of more than 5000 data samples which were collected from a diverse population group that belongs to different age groups (from 4 years to 60 years), genders, educational backgrounds, occupations, communities from three different districts of Manipur, India (Imphal East District, Thoubal District and Kangpokpi District) during March and April 2019.
- Subjects:
- Computing
- Keywords:
- Optical pattern recognition
- Resource Type:
- Others
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This package contains: 1. SUFR-W, a dataset of “in the wild” natural images of faces gathered from the internet. The protocol used to create the dataset is described in Leibo, Liao and Poggio (2014) - https://cbmm.mit.edu/publications/conference-abstracts/subtasks-unconstrained-face-recognition 2. The full set of SUFR synthetic datasets, called the “Subtasks of Unconstrained Face Recognition Challenge” in Leibo, Liao and Poggio (2014) - https://cbmm.mit.edu/publications/conference-abstracts/subtasks-unconstrained-face-recognition
- Subjects:
- Computing
- Keywords:
- Human face recognition (Computer science) Optical pattern recognition
- Resource Type:
- Others