课时1：The Next Step for Machine Learning

课时2：Anomaly Detection (1)

课时3：Anomaly Detection (2)

课时4：Anomaly Detection (3)

课时5：Anomaly Detection (4)

课时6：Anomaly Detection (5)

课时7：Anomaly Detection (6)

课时8：Anomaly Detection (7)

课时9：Attack ML Models (1)

课时10：Attack ML Models (2)

课时11：Attack ML Models (3)

课时12：Attack ML Models (4)

课时13：Attack ML Models (5)

课时14：Attack ML Models (6)

课时15：Attack ML Models (7)

课时16：Attack ML Models (8)

课时17：Explainable ML (1)

课时18：Explainable ML (2)

课时19：Explainable ML (3)

课时20：Explainable ML (4)

课时21：Explainable ML (5)

课时22：Explainable ML (6)

课时23：Explainable ML (7)

课时24：Explainable ML (8)

课时25：Life Long Learning (1)

课时26：Life Long Learning (2)

课时27：Life Long Learning (3)

课时28：Life Long Learning (4)

课时29：Life Long Learning (5)

课时30：Life Long Learning (6)

课时31：Life Long Learning (7)

课时32：Meta Learning – MAML (1)

课时33：Meta Learning – MAML (2)

课时34：Meta Learning – MAML (3)

课时35：Meta Learning – MAML (4)

课时36：Meta Learning – MAML (5)

课时37：Meta Learning – MAML (6)

课时38：Meta Learning – MAML (7)

课时39：Meta Learning – MAML (8)

课时40：Meta Learning – MAML (9)

课时41：Meta Learning - Gradient Descent as LSTM (1)

课时42：Meta Learning - Gradient Descent as LSTM (2)

课时43：Meta Learning - Gradient Descent as LSTM (3)

课时44：Meta Learning – Metric-based (1)

课时45：Meta Learning – Metric-based (2)

课时46：Meta Learning – Metric-based (3)

课时47：Meta Learning - Train+Test as RNN

课时48：More about Auto-encoder (1)

课时49：More about Auto-encoder (2)

课时50：More about Auto-encoder (3)

课时51：More about Auto-encoder (4)

课时52：Network Compression (1)

课时53：Network Compression (2)

课时54：Network Compression (3)

课时55：Network Compression (4)

课时56：Network Compression (5)

课时57：Network Compression (6)

课时58：GAN (Quick Review)

课时59：Flow-based Generative Model

课时60：Transformer

课时61：ELMO, BERT, GPT