This article mainly introduces the basic concepts and processes of machine learning, and recommends some popular machine learning libraries and tools.
Machine learning is a subfield of artificial intelligence that enables computers to learn and make decisions or predictions without being explicitly programmed. Machine learning is divided into three types: supervised learning, unsupervised learning and reinforcement learning.
Supervised learning is to train through labeled data sets to learn the mapping relationship between input and output; unsupervised learning is to discover hidden patterns or structures through unlabeled data sets; reinforcement learning learns strategies by interacting with the environment and receiving feedback of rewards or punishments. The process of machine learning includes data collection, data preprocessing, model selection, model training, model evaluation and model deployment.
For beginners, it is necessary to master the basic knowledge of statistics, linear algebra, calculus and programming, and gain practical experience through practical project application. In the meantime, be curious and keep learning, and network and collaborate with other data scientists.
Popular Machine Learning Libraries and Tools
has many tools and libraries available to simplify the machine learning process. Some popular ML libraries include:
Scikit-learn
Scikit-learn is a widely used machine learning Python library that provides simple and efficient tools for data preprocessing, model selection, training, and evaluation. It supports a variety of supervised and unsupervised learning algorithms, as well as tools for model selection and hyperparameter tuning.
TensorFlow
TensorFlow is an open source library developed by Google for numerical computing and large-scale machine learning. It is especially popular in deep learning, a subfield of machine learning that focuses on multilayer neural networks.
Keras
Keras is a high-level neural network API written in Python that can run on top of TensorFlow, Microsoft Cognitive Toolkit, or Theano. It is designed to enable quick experimentation with deep learning models, and its user-friendly interface makes it ideal for beginners.
PyTorch
PyTorch is an open source deep learning library developed by Facebook that allows dynamic computation graphs, making it more flexible and easier to debug than TensorFlow. It is popular for its simplicity, performance and ease of use.
SAS Viya
SAS Viya is a comprehensive software suite for data management, advanced analytics and predictive modeling. It is one of the oldest and most widely used statistical packages in various industries such as finance, healthcare, and retail. SAS provides an extensive library of machine learning algorithms and data preprocessing techniques, as well as a user-friendly interface that can be used by both novice and experienced data scientists. While SAS isn't as open source as the other libraries mentioned above, it's still a popular choice among organizations that prioritize stability, support, and scalability.
