Vidooly Data Science Internship Program 2020

Vidooly Data Science Internship 2020 :

About Vidooly :
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Vidooly is an online video analytics company based in India. It was launched in November 2014 and currently, more than 50,000 online video creators, 50 multi-channel networks, 50+ multi-platforms, and 20 brands/agencies use its dashboards on a daily basis. Our vision is to build technology that tracks and analyzes every video, everywhere on the planet to make sense of business for content creators, brands & media buyers and at the same time creating a universal video data repository which can be accessed by our customers for better media planning, advertisement & strategies.

Job Profile : Data Science Intern

Experience : Freshers

Duration : 3 Months

About the Internship:

Selected intern’s day-to-day responsibilities include:

1. Handling data mining for structured and unstructured data
2. Building and evaluating models for machine/deep learning
3. Working on image/object recognition/detection using deep learning
4. Working on text analysis using natural language processing
5. Handling data set creation/data collection
6. Working on image labeling
7. Working on manual lagging
8. Testing APIs
9. Coding on various programming languages (if required)

Skill(s) required: Python , SQL and Machine Learning
Who can apply:

Only those candidates can apply who:

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  1. are available for full time (in-office) internship
  2. an start the internship between 28th Aug’20 and 2nd Oct’20
  3. are available for duration of 3 months
  4. have relevant skills and interests
Requirements :
  1. Must have a BS in computer science, software engineering, statistics, calculus, and algebra or a related course
  2. Must be good at Python and its frameworks (such as NumPy, Pandas, Matplotlib, or Scikit) or R
  3. Must have proficiency in using SQL and knowledge of database architecture
  4. Must have deep knowledge of machine learning, deep learning (convolutional networks, recurrent networks such as LSTM, GRU, etc.), computer vision, and NLP
  5. Must have experience with the data mining and statistical tools and algorithms
  6. Must have knowledge of big data, cloud computing technologies, distributed systems, recommendation systems, and pattern recognition
  7. Must have used at least one deep learning library (TensorFlow, Caffe, Theano, Torch, etc.)
  8. Must have a data structure and algorithm expertise
  9. Must have good Kaggle/GitHub/Stack Overflow profile/projects

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