Optimizing bitrate adaption to sudden bandwidth changes based on inferred network characteristics

One or more processors and a memory configured to perform operations comprising:

• decoding network data representing an available bandwidth for a transmission;
• determining, based on the network data, that the available bandwidth will change from a first bandwidth level to a second bandwidth level, wherein detecting that the available bandwidth will change from the first bandwidth level to the second bandwidth level comprises executing a first machine learning engine that is trained with training data that associates values of the network data with changes in the available bandwidth for the transmission, wherein the change from the first bandwidth level to the second bandwidth level exceeds a threshold that set based on training of the first machine learning engine;
• classifying that the network is congested or not congested, wherein classifying that the network is congested or not congested comprises executing a second machine learning engine that is trained with training data that associates values of the network data with congestion levels for the network, wherein a threshold probability level that represents that the network is congested is set based on training of the second machine learning engine;
• when the network is classified as congested, adjusting a bitrate for the transmission to a first value that enables network congestion to clear;
• or
• when the network is classified as non-congested, adjusting the bitrate for the transmission to a second value that fully utilizes the second bandwidth level.