Data Science (Machine Learning) Internship in Noida at Vidooly
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Data Science (Machine Learning)
Start Date
Starts immediatelyImmediately
6 Months
10000-12000 /month
Apply By
14 Jun' 19
About Vidooly
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. Some of our popular customers include GroupM, Xaxis, Mindshare, Tata Housing, OML, Videogyan, History TV India, TVF Qtiyapa, Times Music, and many more. Funded and backed by GVFL, Times Internet & Bessemer Venture Partners, Vidooly is the only online video analytics company in India & South East Asia.
About the internship
Selected intern's day-to-day responsibilities include:

1. Handle data mining for structured and unstructured data
2. Build and evaluate models for machine/deep learning
3. Work on image/object recognition/detection using deep learning
4. Work on text analysis using natural language processing

What would the intern learn in this internship?

1. Get an opportunity to work with the super talented team
2. Develop learning and a comprehensive understanding of the overall video ecosystem and analytics
3. Learn a lot about how a business works
Skill(s) required
Python Machine Learning
Learn these skills on Internshala Trainings
Who can apply

Only those candidates can apply who:

1. are available for full time (in-office) internship

2. can start the internship between 31st May'19 and 30th Jun'19

3. are available for duration of 6 months

4. have relevant skills and interests

Other requirements

1. Should have a BS in computer science, software engineering, statistics, calculus, and algebra or a related course

2. Should be good at Python and its frameworks (such as NumPy, Pandas, Matplotlib, or Scikit) or R

3. Should have proficiency in using SQL and knowledge of database architecture

4. Should have deep knowledge of machine learning, deep Learning (convolutional networks, recurrent networks such as LSTM, GRU, etc.), computer vision, and NLP

5. Should have experience with the data mining and statistical tools and algorithms

6. Should 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. Should have good Kaggle/GitHub/Stack Overflow profile/projects

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