Strang刚出了一本新书叫《Linear Algebra and Learning From Data》[1]，我刚开始读，但到目前为止觉得挺过瘾的。它风格既像拉家常又相当简明扼要（类似《All of Statistics》）。里面讲了很多高深且非常前沿的……
Strang just published a new book called "Linear Algebra and Learning From Data" [1] which I only just started but find to be quite enjoyable so far. It's simultaneously conversational but also quite terse (similar to "All of Statistics"). There are many advanced and very contemporary…
去看看Gilbert Strang写的《Linear Algebra and Learning from Data》。它包含对线性代数的极佳入门，涵盖了相关的统计学和最优化，然后用神经网络的章节把它们全部串起来。这是一本教材，所以……
Check out "Linear Algebra and Learning from Data" by Gilbert Strang. It includes a nice introduction to Linear Algebra, touches on relevant statistics and optimization, then puts them all together in chapters on neural networks. It's a textbook, so…
想找一个真正直观的线性代数入门，我强烈推荐Gilbert Strang的《Linear Algebra and Learning from Data》：https://math.mit.edu/~gs/learningfromdata/
For a really intuitive introduction to linear algebra, I highly recommend Gilbert Strang's "Linear Algebra and Learning from Data": https://math.mit.edu/~gs/learningfromdata/
……深度学习。- MIT OCW 课程：数据分析、信号处理与机器学习中的矩阵方法 (https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-an...) - 教材主页：Linear Algebra and Learning from Data (2019) https://math.mit.edu/~gs/learningfromdata/ - 经典线性代数课程：https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010...
…of deep learning. - MIT OCW Course: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-an...) - The text book website: Linear Algebra and Learning from Data (2019) https://math.mit.edu/~gs/learningfromdata/ - The Classic Linear Algebra Course: https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010...
如果你喜欢3B1B，并且偏好重直觉/重应用的视角，那选Strang绝对胜过Axler。特别是去翻翻他较新的教材《Linear Algebra and Learning from Data》。Axler更偏向纯数教材——如果你想更多地钻研证明和抽象概念的话。
If you liked 3B1B and prefer intuition/applications-heavy view, then definitely Strang over Axler. Check out especially his newer textbook Linear Algebra and Learning from Data. Axler is more of a pure math textbook - if you want to lean more into proofs and abstractions.
这是他即将出版的新书以及几周后会上线的MIT新课视频链接：Linear Algebra and Learning from Data http://math.mit.edu/~gs/learningfromdata/
Here's the link for his upcoming book and new MIT course videos that be will posted online in a few weeks: Linear Algebra and Learning from Data http://math.mit.edu/~gs/learningfromdata/
Strang刚出了一本新书叫《Linear Algebra and Learning From Data》[1]，我刚开始读，但到目前为止觉得挺过瘾的。它风格既像拉家常又相当简明扼要（类似《All of Statistics》）。里面讲了很多高深且非常前沿的……
Strang just published a new book called "Linear Algebra and Learning From Data" [1] which I only just started but find to be quite enjoyable so far. It's simultaneously conversational but also quite terse (similar to "All of Statistics"). There are many advanced and very contemporary…
去看看Gilbert Strang写的《Linear Algebra and Learning from Data》。它包含对线性代数的极佳入门，涵盖了相关的统计学和最优化，然后用神经网络的章节把它们全部串起来。这是一本教材，所以……
Check out "Linear Algebra and Learning from Data" by Gilbert Strang. It includes a nice introduction to Linear Algebra, touches on relevant statistics and optimization, then puts them all together in chapters on neural networks. It's a textbook, so…
想找一个真正直观的线性代数入门，我强烈推荐Gilbert Strang的《Linear Algebra and Learning from Data》：https://math.mit.edu/~gs/learningfromdata/
For a really intuitive introduction to linear algebra, I highly recommend Gilbert Strang's "Linear Algebra and Learning from Data": https://math.mit.edu/~gs/learningfromdata/
……深度学习。- MIT OCW 课程：数据分析、信号处理与机器学习中的矩阵方法 (https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-an...) - 教材主页：Linear Algebra and Learning from Data (2019) https://math.mit.edu/~gs/learningfromdata/ - 经典线性代数课程：https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010...
…of deep learning. - MIT OCW Course: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-an...) - The text book website: Linear Algebra and Learning from Data (2019) https://math.mit.edu/~gs/learningfromdata/ - The Classic Linear Algebra Course: https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010...
如果你喜欢3B1B，并且偏好重直觉/重应用的视角，那选Strang绝对胜过Axler。特别是去翻翻他较新的教材《Linear Algebra and Learning from Data》。Axler更偏向纯数教材——如果你想更多地钻研证明和抽象概念的话。
If you liked 3B1B and prefer intuition/applications-heavy view, then definitely Strang over Axler. Check out especially his newer textbook Linear Algebra and Learning from Data. Axler is more of a pure math textbook - if you want to lean more into proofs and abstractions.
这是他即将出版的新书以及几周后会上线的MIT新课视频链接：Linear Algebra and Learning from Data http://math.mit.edu/~gs/learningfromdata/
Here's the link for his upcoming book and new MIT course videos that be will posted online in a few weeks: Linear Algebra and Learning from Data http://math.mit.edu/~gs/learningfromdata/