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Data Science Techniques involve a variety of quantitative and qualitative methods used to extract insights from data. It is a field that leverages statistical analysis, machine learning algorithms, and big data tools to identify patterns and trends in datasets. The techniques can be applied to various domains such as finance, healthcare, marketing, and social media. In the context of Machine Learning, Data Science Techniques encompass supervised and unsupervised learning methods, feature engineering, model evaluation, and selection. These techniques are used to build predictive models that can learn from data and make accurate predictions or decisions without being explicitly programmed. Overall, Data Science Techniques enable organizations to make informed decisions based on data-driven insights and drive business value by unlocking the potential of their data assets.