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fixed some slides links #212

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4 changes: 2 additions & 2 deletions contents/data_engineering/data_engineering.qmd
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Expand Up @@ -469,9 +469,9 @@ Here is a curated list of resources to support students and instructors in their

These slides are a valuable tool for instructors to deliver lectures and for students to review the material at their own pace. We encourage students and instructors to leverage these slides to enhance their understanding and facilitate effective knowledge transfer.

* [Data Engineering: Overview.](https://docs.google.com/presentation/d/1nuNFjB99ccE6hqFeAmRRbhoEoSjBgJXGr9u6cvwnXgM/edit#slide=id.p19)
* [Data Engineering: Overview.](https://docs.google.com/presentation/d/1jlIfD6RtQWG8314jCAu1qdnG7YyESy60Yt5-zXhEsVA/edit#slide=id.g202a7c05d1a_0_0)

* [Feature engineering.](https://docs.google.com/presentation/d/1otnrLjtBOGmrT-FBzAGajRwXJTC65OQCpGCxjxCzn_k/edit#slide=id.p1)
* [Feature engineering.](https://docs.google.com/presentation/d/1AIM1H-GfvjNPHQw9urxJz3vtMgb_9kizfthbymISPR4/edit#slide=id.g202a83498d1_0_0)

* [Data Standards: Speech Commands.](https://docs.google.com/presentation/d/1qDoHc7yzZ2lEha9NTMZ07Ls4tkIz-1f7kUYRlvjzsI4/edit?usp=drive_link&resourcekey=0-ol4Oqk_y706P_zIB5mbu7Q)

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10 changes: 4 additions & 6 deletions contents/frameworks/frameworks.qmd
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Expand Up @@ -739,15 +739,13 @@ Here is a curated list of resources to support students and instructors in their

These slides are a valuable tool for instructors to deliver lectures and for students to review the material at their own pace. We encourage students and instructors to leverage these slides to enhance their understanding and facilitate effective knowledge transfer.

* [Why do we need frameworks?](https://docs.google.com/presentation/d/1zbnsihiO68oIUE04TVJEcDQ_Kyec4mhdQkIG6xoR0DY/edit#slide=id.p1)
* [Frameworks overview.](https://docs.google.com/presentation/d/1zbnsihiO68oIUE04TVJEcDQ_Kyec4mhdQkIG6xoR0DY/edit#slide=id.g1ff94734162_0_0)

* [Frameworks overview.](https://docs.google.com/presentation/d/1Ruibe1cvo0LhOM4GgFinR_z9IlJgZ7EX3snj8LriV-8/edit)
* [Embedded systems software.](https://docs.google.com/presentation/d/1BK2M2krnI24jSWO0r8tXegl1wgflGZTJyMkjfGolURI/edit#slide=id.g202a6885eb3_0_0)

* [Embedded systems software.](https://docs.google.com/presentation/d/1-hpejUcj4PJ6Sm8dncBm6ngUwYsBevj9jmdonfy0f8g/edit#slide=id.p1)
* [Inference engines: TF vs. TFLite.](https://docs.google.com/presentation/d/1Jr7HzdZ7YaKO6KY9HBGbOG0BrTnKhbboQtf9d6xy3Ls/edit?usp=drive_link)

* [Inference engines: TF vs. TFLite.](https://docs.google.com/presentation/d/12IlNZx75Z-NRK2rAO4xs5qmD7lU0h8eMibkpWPvZwHY/edit#slide=id.p1)

* [TF flavors: TF vs. TFLite vs. TFLite Micro.](https://docs.google.com/presentation/d/1Gt-mhBZueCUXq1_I7qFTY8s6udDHw0ncbkQ3ZsaXCjA/edit#slide=id.p1)
* [TF flavors: TF vs. TFLite vs. TFLite Micro.](https://docs.google.com/presentation/d/1_DwBbas8wAVWnJ0tbOorqotf9Gns1qNc3JJ6tw8bce0/edit?usp=drive_link)

* TFLite Micro:
* [TFLite Micro Big Picture.](https://docs.google.com/presentation/d/1XdwcZS0pz6kyuk6Vx90kE11hwUMAtS1cMoFQHZAxS20/edit?usp=drive_link)
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8 changes: 4 additions & 4 deletions contents/ops/ops.qmd
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Expand Up @@ -883,13 +883,13 @@ These slides serve as a valuable tool for instructors to deliver lectures and fo

* [MLOps, DevOps, and AIOps.](https://docs.google.com/presentation/d/1vsC8WpmvVRgMTpzTltAhEGzcVohMkatMZBqm3-P8TUY/edit?usp=drive_link)

* [MLOps overview.](https://docs.google.com/presentation/d/1tG7YfW-FwC5Up3gLk-DrvOkpKmkMPO6y2k-t7FJgK3s/edit#slide=id.p1)
* [MLOps overview.](https://docs.google.com/presentation/d/1GVduKipd0ughTpqsHupGqAPW70h0xNOOpaIeSqLOc1M/edit?usp=drive_link)

* [Tiny MLOps.](https://docs.google.com/presentation/d/1Sa27wZmKokVyKwmLLM2p_HHAam-sXKVPxzxqv-0y2V8/edit)
* [Tiny MLOps.](https://docs.google.com/presentation/d/1MNjVOcx5f5Nfe3ElDqTxutezcGXm4yI8PkjWOuQYHhk/edit?usp=drive_link)

* [MLOps: a use case.](https://docs.google.com/presentation/d/1qhBZvtHe5jya6TAAmZKlK2oowQUfBwhIOcfk1fpoGq4/edit?resourcekey=0-xKK09GAhYbOK6dB_RrSvkw#slide=id.ged8f947d63_0_0)
* [MLOps: a use case.](https://docs.google.com/presentation/d/1449rzplaL0lOPoKh0mrpds3KPPoOHWdR5LIZdd7aXhA/edit#slide=id.g2ddfdf6e85f_0_0)

* [MLOps: Key Activities and Lifecycle.](https://docs.google.com/presentation/d/1awWKlEYyYcHp5HR5MXomg0v6uevtvFV76HjesxrN_9g/edit#slide=id.geb6aec3278_0_0)
* [MLOps: Key Activities and Lifecycle.](https://docs.google.com/presentation/d/1vGCffLgemxTwTIo7vUea5CibOV7y3vY3pkJdee-y5eA/edit#slide=id.g2de2d5f2ac0_0_0)

* [ML Lifecycle.](https://docs.google.com/presentation/d/1FW8Q1Yj5g_jbArFANfncbLQj36uV2vfV8pjoqaD6gjM/edit#slide=id.g94db9f9f78_0_2)

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10 changes: 5 additions & 5 deletions contents/optimizations/optimizations.qmd
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Expand Up @@ -955,21 +955,21 @@ These slides serve as a valuable tool for instructors to deliver lectures and fo

* [Quantization: Part 2.](https://docs.google.com/presentation/d/18oLTdwa-dZxbBNpvHzZVyMS8bUbed4ao/edit?usp=drive_link&ouid=102419556060649178683&rtpof=true&sd=true)

* [Post-Training Quantization (PTQ).](https://docs.google.com/presentation/d/1pH_fkSezVRrVsX2uorC8prqTtOh-R7BBOPvth_KdanU/edit#slide=id.p1)
* [Post-Training Quantization (PTQ).](https://docs.google.com/presentation/d/1eSOyAOu8Vg_VfIHZ9gWRVjWnmFTOcZ4FavaNMc4reHQ/edit)

* [Quantization-Aware Training (QAT).](https://docs.google.com/presentation/d/1bLNMHGEhhP7tAp7-FWM3zqDXycRhGBnNp6R_Ov5jVUA/edit#slide=id.p1)
* [Quantization-Aware Training (QAT).](https://docs.google.com/presentation/d/1qvoKLjKadK1abqUuuCCy9gaTynMZivDKLbV2Hjftri8/edit?usp=drive_link)

* Pruning:
* [Pruning: Part 1.](https://docs.google.com/presentation/d/1KX_I71smbztdqycPXBDAYjShinrTtQeF/edit#slide=id.p1)

* [Pruning: Part 2.](https://docs.google.com/presentation/d/1kZGDhnkeRcAw1pz3smO837ftotXQEiO7/edit?usp=drive_link&ouid=102419556060649178683&rtpof=true&sd=true)

* [Knowledge Distillation.](https://docs.google.com/presentation/d/1SXjA3mCSwKmdouuWoxSk7r-Yjd67RG7i/edit#slide=id.p17)
* [Knowledge Distillation.](https://docs.google.com/presentation/d/1SXjA3mCSwKmdouuWoxSk7r-Yjd67RG7i/edit#slide=id.g202a77b5f4f_0_110)

* [Clustering.](https://docs.google.com/presentation/d/1ku1MJnfKoueoH8NEWP1o90XNNn61iOiaKJdtT7JDCrM/edit)
* [Clustering.](https://docs.google.com/presentation/d/14K9QFUjiba1NvwG0zobsJdgEklomuM_xeaCP7-5dmY8/edit?usp=drive_link)

* Neural Architecture Search (NAS):
* [NAS overview.](https://docs.google.com/presentation/d/15E5-dL0v6YT8WvWKEXd1HCXNvlGFcVDvMo1aO_pCfCs/edit#slide=id.p1)
* [NAS overview.](https://docs.google.com/presentation/d/1aVGjhj1Q-_JEFHr6CYzPeuMOCiDivzhZCBtg1xV14QM/edit#slide=id.g202a67d8ddf_0_0)

* [NAS: Part 1.](https://docs.google.com/presentation/d/1V-ZD6c8KPrFBrrw8xkAQfkqUu4u53zkX/edit?usp=drive_link&ouid=102419556060649178683&rtpof=true&sd=true)

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4 changes: 2 additions & 2 deletions contents/privacy_security/privacy_security.qmd
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Expand Up @@ -1102,9 +1102,9 @@ Here is a curated list of resources to support students and instructors in their

These slides are a valuable tool for instructors to deliver lectures and for students to review the material at their own pace. We encourage students and instructors to leverage these slides to enhance their understanding and facilitate effective knowledge transfer.

* [Security.](https://docs.google.com/presentation/d/1wFUfVe5CXb_nzjUVpSPsGqXJC61ZuQLhnczKgidx4kE/edit#slide=id.p1)
* [Security.](https://docs.google.com/presentation/d/1jZBi8DS1NUXFdIwNGwofzA4CYRei6lH2e56BOu098-k/edit#slide=id.g1ff987f3d96_0_0)

* [Privacy.](https://docs.google.com/presentation/d/1uZBAlcxrDrWY9TTQN7RffusBnMp4WXtuJaHA2VjynbY/edit#slide=id.p1)
* [Privacy.](https://docs.google.com/presentation/d/1Wp-5eO4Bmco2f7ppNKsRkE1utuz22PeLvVoREFSChR8/edit#slide=id.g202a5aaf418_0_0)

* [Monitoring after Deployment.](https://docs.google.com/presentation/d/1WlQdk40zJcW9Bx6ua-vKu3sDrMU_iI89BQGMGk6OEB0/edit?usp=drive_link)

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2 changes: 1 addition & 1 deletion contents/workflow/workflow.qmd
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Expand Up @@ -117,7 +117,7 @@ These slides are a valuable tool for instructors to deliver lectures and for stu

* [ML Workflow.](https://docs.google.com/presentation/d/1rWXLegepZjpJHonYLKcOJYfOIunmOBnrg0SGhy1pZ_I/edit)

* [ML Lifecycle.](https://docs.google.com/presentation/d/1P-h2Zi0FzyA3TvV3oezjpcSylzEbts9b3uKS07_lF4A/edit)
* [ML Lifecycle.](https://docs.google.com/presentation/d/1zOxDX-tKlY8t9KmCYek0E-mZA9ENPjW9ymVyFV17DmE/edit)

:::

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