Machine learning algorithms for time series analysis
It mainly depends on the task you are looking to accomplish with your time series data. Is it a regression or a classification task. In general, Random Forests are known to be easy to use and pretty useful. So I think it's a good way to start. Of course, dimensionality reduction techniques and feature extractors like PCA, kernel PCA, t-SNE and many others are very useful if you want to get better results. Neural networks are also useful, depending on the task you can try both recurrent (LSTM) or convolutional NN.