大数据和机器学习的区别

大数据：是指大型组织和企业获得的庞大、庞大或海量的数据、信息或相关统计数据。由于难以手动计算大数据，因此创建和准备了许多软件和数据存储。它用于发现模式和趋势，并做出与人类行为和交互技术相关的决策。

机器学习：机器学习是人工智能的一个子集，它有助于在没有明确编程的情况下自动学习和改进系统。机器学习使用算法来处理数据并接受培训，以便在无需人工干预的情况下提供未来预测。机器学习的输入是一组指令或数据或观察。

下表列出了大数据和机器学习之间的差异：

Big Data	Machine Learning
Big Data is more of extraction and analysis of information from huge volumes of data.	Machine Learning is more of using input data and algorithms for estimating unknown future results.
Types of Big Data are Structured, Unstructured and Semi-Structured.	Types of Machine Learning Algorithms are Supervised Learning and Unsupervised Learning, Reinforcement Learning.
Big data analysis is the unique way of handling bigger and unstructured data sets using tools like Apache Hadoop, MongoDB.	Machine Learning is the way of analysing input datasets using various algorithms and tools like Numpy, Pandas, Scikit Learn, TensorFlow, Keras.
Big Data analytics pulls raw data and looks for patterns to help in stronger decision-making for the firms	Machine Learning can learn from training data and acts like a human for making effective predictions by teaching itself using Algorithms.
It’s very difficult to extract relevant features even with latest data handling tools because of high-dimensionality of data.	Machine Learning models work with limited dimensional data hence making it easier for recognizing features
Big Data Analysis requires Human Validation because of large volume of multidimensional data.	Perfectly built Machine Learning Algorithms does not require human intervention.
Big Data is helpful for handling different purposes including Stock Analysis, Market Analysis, etc.	Machine Learning is helpful for providing virtual assistance, Product Recommendations, Email Spam filtering, etc.
The Scope of Big Data in the near future is not just limited to handling large volumes of data but also optimizing the data storage in a structured format which enables easier analysis.	The Scope of Machine Learning is to improve quality of predictive analysis, faster decision making, more robust, cognitive analysis, rise of robots and improved medical services.