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Machine Learning and Artificial Intelligence Hub - Courses, Projects and Resources

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All courses, projects and resources on Machine Learning and Artificial Intelligence that I have curated personally and always growing over the period of time. Anyone hoping to pursue through the Machine Learning and Artificial Intelligence industry, I hope might find the content helpful in learning, improving their skills and grow their experience or just find tools that might aid in the process.

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  • YOLOv7 Multi-Person Pose Estimation - Multi-Person Pose Estimation using YOLOv7.

  • Food Vision - Food vision project on Food101 dataset using transfer learning based on EfficienetNetB0 backbone with TensorFlow. The goal of beating DeepFood, a 2016 paper which used a Convolutional Neural Network trained for 2-3 days to achieve 77.4% top-1 accuracy.

  • SkimLit - Replicated the deep learning model behind the 2017 paper PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts. The goal of the dataset was to explore the ability for NLP models to classify sentences which appear in sequential order.

  • Dog Vision - Classify Different Dog Breeds using Transfer Learning and TensorFlow. Used data from the Kaggle dog breed identification competition. It consists of a collection of 10,000+ labelled images of 120 different dog breeds.

  • EDA Bank Loan Default Risk Analysis - The case study aims to provide an idea of applying EDA in a real business scenario. In this case study, apart from applying the techniques that you have learnt in the EDA module, you will also develop a basic understanding of risk analytics in banking and financial services and understand how data is used to minimise the risk of losing money while lending to customers.

  • Weather Prediction using Neural Network - Hackmakers Formula AI Hackathon 2022: Weather Prediction using Neural Network.

  • E-Commerce Dataset Analysis - Use skills and understanding of HIVE and Hadoop concepts to extract data, load data into HIVE tables and gather insights from the data set.

  • US Patent Phrase to Phrase Matching - Kaggle challenge to train a model on a novel semantic similarity dataset to extract relevant information by matching key phrases in patent documents.

  • Deep Neural Networks Examples - Deep Neural Network examples to represent different concepts in Deep Neural Networks. Projects/Examples part of the Deep Learning Specialization.

  • Market Basket Analysis using Apriori Algorithm & PySpark - Market Basket Analysis is a data mining technique that helps to understand the relationship between the items sold by the company. As the name suggests, the method tries to analyse the customer basket or the transaction data to identify any association between items. The results from this analysis help the companies to develop marketing strategies to increase their revenue by gaining insight into which items are frequently purchased together by customers. This project aims at doing Market Basket Analysis using Apriori Algorithm & PySpark.

Awesome Machine Learning Python Libraries

Best-of Machine Learning with Python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. This curated list contains 900 awesome open-source projects with a total of 3.4M stars grouped into 34 categories.

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