Deep Learning Internship

Role Overview: You will be responsible for building deep learning models using TensorFlow/PyTorch and collaborating with the team to ensure proper testing and deployment. Your role will involve applying your knowledge of Deep Learning Algorithms in both NLP (LSTMs, RNNs, etc.) and Computer Vision (CNNs, etc.) domains to solve real-life problems. Additionally, you will be creating and updating documentation for the work done and implementing deep learning algorithms from scratch. Key Responsibilities: - Research on machine learning/data science topics and write articles for the company websites - Assist with hands-on coding on Jupyter Notebook for providing code snippets in the articles - Work on short projects, assignments, and deployment techniques - Design and implement machine learning, information extraction, probabilistic matching algorithms, and models - Utilize programming skills and deep learning/AI expertise using Python, TensorFlow, Keras, and PyTorch to solve real-life problems - Develop AI solutions in the computer vision domain using CNN and a combination of deep neural networks - Solve object detection, recognition, image classification problems using machine learning and deep learning algorithms - Implement transfer learning methods and techniques - Use innovative and automated approaches for data annotation, labeling, and data augmentation - Provide online code assistance, code mentoring, and education-based solutions Qualifications Required: - Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience - Relevant internship or work experience with data analysis - Experience with statistical software (R, Python, S-Plus, SAS, or similar) and database languages (e.g., SQL) - Preferred qualifications include a Master's or B.Tech in relevant fields Additional Details: The company offers perks such as Certificates, Letters of recommendation, Flexible work hours, Informal dress code, 5 days a week, and Free snacks & beverages. Role Overview: You will be responsible for building deep learning models using TensorFlow/PyTorch and collaborating with the team to ensure proper testing and deployment. Your role will involve applying your knowledge of Deep Learning Algorithms in both NLP (LSTMs, RNNs, etc.) and Computer Vision (CNNs, etc.) domains to solve real-life problems. Additionally, you will be creating and updating documentation for the work done and implementing deep learning algorithms from scratch. Key Responsibilities: - Research on machine learning/data science topics and write articles for the company websites - Assist with hands-on coding on Jupyter Notebook for providing code snippets in the articles - Work on short projects, assignments, and deployment techniques - Design and implement machine learning, information extraction, probabilistic matching algorithms, and models - Utilize programming skills and deep learning/AI expertise using Python, TensorFlow, Keras, and PyTorch to solve real-life problems - Develop AI solutions in the computer vision domain using CNN and a combination of deep neural networks - Solve object detection, recognition, image classification problems using machine learning and deep learning algorithms - Implement transfer learning methods and techniques - Use innovative and automated approaches for data annotation, labeling, and data augmentation - Provide online code assistance, code mentoring, and education-based solutions Qualifications Required: - Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience - Relevant internship or work experience with data analysis - Experience with statistical software (R, Python, S-Plus, SAS, or similar) and database languages (e.g., SQL) - Preferred qualifications include a Master's or B.Tech in relevant fields Additional Details: The company offers perks such as Certificates, Letters of recommendation, Flexible work hours, Informal dress code, 5 days a week, and Free snacks & beverages.