機械学習、人工知能（Deep Learning）関連のトレーニングにおいて、次のCertificationを取得しております。
・Deep Learning
1. Deep Learning and Newral Network
２. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
3. Structuring Machine Learning Projects
4. Convolutional Neural Networks
https://medium.com/@takuyayamauchi/deep-learning-6d56dd5c3382
・Tensor Flow 関連
1. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
2. Convolutional Neural Networks in TensorFlow
3. Natural Language Processing in TensorFlow
4. Sequences, Time Series and Prediction
https://medium.com/@takuyayamauchi/tensorflow-in-practice-6cd15dd6f309
・Machine Learning (Stanford Andrew Ng)
機械学習について 以下、抜粋です。
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
