Code generated in the video can be downloaded from here: https://github.com/bnsreenu/py....thon_for_microscopis

Special Thanks To Ashish Patel And All The Bloggers For the Amazing Contribution
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https://github.com/ashishpatel....26/500-AI-Machine-le
⭐ Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite for a few months and I love it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=krishnaik&utm_content=description-only

Starter In Data Science

1 Complete Machine Learning Playlist:(Top 24 videos)

https://www.youtube.com/playli....st?list=PLZoTAELRMXV

2 Statistics in Machine Learning:(Understand some Concepts With Respect To Data)- Complete Playlist
https://www.youtube.com/playli....st?list=PLZoTAELRMXV

3. Feature Engineering(Complete Playlist)
https://www.youtube.com/playli....st?list=PLZoTAELRMXV

4. Continue The Complete Machine Learning Playlist(24-all the videos)

5. Live Stream Playlist:(Top 10 videos)
https://www.youtube.com/playli....st?list=PLZoTAELRMXV

6. Machine Learning Pipelines

https://www.youtube.com/playli....st?list=PLZoTAELRMXV

7. Complete Deep Learning Playlist:
Tensorflow And Keras-https://www.youtube.com/playli....st?list=PLZoTAELRMXV

Pytorch: https://www.youtube.com/playli....st?list=PLZoTAELRMXV

8. Live Projects Playlist:
https://www.youtube.com/playli....st?list=PLZoTAELRMXV
9. Live stream Playlist: https://www.youtube.com/playli....st?list=PLZoTAELRMXV
10.Docker Playlist: https://www.youtube.com/playli....st?list=PLZoTAELRMXV
11. Mongodb: https://www.youtube.com/playli....st?list=PLZoTAELRMXV
12. Machine Learning Interviews: https://www.youtube.com/playli....st?list=PLZoTAELRMXV

Deeplearning4j is one of the few libraries that allows you to train your net over a distributed, multi-node cluster. The library provides an Iterative Map-Reduce procedure as well as a set of tools for configuring a Deep Net using hyper-parameters.

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The Deeplearning4j Java library was created by Adam Gibson in response to the lack of distributed, multi-node capabilities in other Deep Net libraries. Deeplearning4j can run on both Scala and Clojure, and it provides built-in GPU support for a distributed framework. You can also use the library to set up a deep net by configuring its hyper-parameters.

Deeplearning4j supports nearly every type of deep net, including the MLP, RBM/DBN, Convolutional Net, Recurrent Net, RNTN, and autoencoders. In addition, the Canova vectorization library is included with the package.

How does the Iterative Map-Reduce procedure differ from standard Map-Reduce? In Deeplearning4j, there are two different steps:

- MAP: Input data is distributed throughout the cluster, with every node receiving a different portion of the data. Each node begins training with its input set.
- REDUCE: After training, the parameters of all the nets are averaged. Every node overwrites its net’s parameters with this global average.

These two steps are repeated iteratively until the error is sufficiently small.

Have you ever trained a deep net over a distributed architecture? Please comment and share your experiences.

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01:01:29 Dataset Link and Jam board Link


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This is a clip from a conversation with Bjarne Stroustrup from Nov 2019. New full episodes are released once or twice a week and 1-2 new clips or a new non-podcast video is released on all other days. You can watch the full conversation here: https://www.youtube.com/watch?v=uTxRF5ag27A
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Note: I select clips with insights from these much longer conversation with the hope of helping make these ideas more accessible and discoverable. Ultimately, this podcast is a small side hobby for me with the goal of sharing and discussing ideas. I did a poll and 92% of people either liked or loved the posting of daily clips, 2% were indifferent, and 6% hated it, some suggesting that I post them on a separate YouTube channel. I hear the 6% and partially agree, so am torn about the whole thing. I tried creating a separate clips channel but the YouTube algorithm makes it very difficult for that channel to grow. So for a little while, I'll keep posting clips on this channel. I ask for your patience and to see these clips as supporting the dissemination of knowledge contained in nuanced discussion. If you enjoy it, consider subscribing, sharing, and commenting.

Bjarne Stroustrup is the creator of C++, a programming language that after 34 years is still one of the most popular and powerful languages in the world. Its focus on fast, stable, robust code underlies many of the biggest systems in the world that we have come to rely on as a society. If you're watching this on YouTube, many of the critical back-end component of YouTube are written in C++. Same goes for Google, Facebook, Amazon, Twitter, most Microsoft applications, Adobe applications, most database systems, and most physical systems that operate in the real-world like cars, robots, rockets that launch us into space and one day will land us on Mars.

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