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title>Jovian/title>
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name>Jovian/name>
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title>Jovian's Batch of November 2023 Graduation Day!/title>
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author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
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published>2023-11-01T14:30:10+00:00/published>
updated>2024-03-14T12:11:55+00:00/updated>
media:group>
media:title>Jovian's Batch of November 2023 Graduation Day!/media:title>
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media:description>Join us for Jovian’s Data Science Bootcamp Graduation Day
Over the past eight months, participants of the program have spent 600+ hours learning data science & machine learning and building real-world projects. Join us to congratulate the graduates and celebrate the fantastic work done by the Jovian community.
List of Speakers
00:00:00 - Introduction
00:00:21 - Pragya Khatri
00:02:51 - Manjunath Reddy
00:05:38 - Haridev S
00:08:33 - Kris Holmquist
00:11:16 - Prabhakar Rawat
00:14:29 - Nnaemeka Hillary Onah
00:17:17 - Saurabh Pati Tripathi
00:20:23 - Anshika Nigam
00:23:09 - Sarthak Srivastava
00:26:02 - Mahima Srivastava
00:29:40 - Chinmaye Chinnappa H E
00:32:36 - Thank you/media:description>
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yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Jovian's Batch of September 2023 Graduation Day!/title>
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author>
name>Jovian/name>
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published>2023-09-11T14:30:10+00:00/published>
updated>2024-03-15T16:46:36+00:00/updated>
media:group>
media:title>Jovian's Batch of September 2023 Graduation Day!/media:title>
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media:description>Join us for Jovian’s Data Science Bootcamp Graduation Day
Over the past eight months, participants of the program have spent 600+ hours learning data science & machine learning and building real-world projects. Join us to congratulate the graduates and celebrate the fantastic work done by the Jovian community.
List of Speakers
00:00:00 - Introduction
00:00:23 - Suraj D
00:03:07 - Joyesh Meshram
00:05:43 - Anjali Ramesh
00:09:40 - Bhavya Bajaj
00:12:22 - Ahlenoor Khan
00:15:02 - Tuan Nguyen
00:17:43 - Sneha Bajaj
00:20:37 - Abhishek Bhardwaj
00:23:37 - Aehtajaz Ahmed
00:26:37 - Thank you/media:description>
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id>yt:video:kFUKx4Rh5CI/id>
yt:videoId>kFUKx4Rh5CI/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Difference between Pass by Value, Pass by Reference | #python #pythonprogramming #pythonlanguage/title>
link rel="alternate" href="https://www.youtube.com/watch?v=kFUKx4Rh5CI"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
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published>2023-06-30T14:30:08+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>Difference between Pass by Value, Pass by Reference | #python #pythonprogramming #pythonlanguage/media:title>
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media:description>📍 📍 Did you know the way you pass arguments to a function can make a huge difference in your code? Let's explore. Pass by value, pass by reference, and how Python handle these concepts.
📍 When you pass an argument by value, a copy of the value is sent to the function.
Any changes made within the function doesn't affect the original variable.
When you pass an argument by reference,
you are passing the memory address of the variable.
Changes made within the function directly affect the original variable
now these concepts are very commonly used in languages like 📍 C, 📍 C plus plus 📍 PHP, et cetera, but
python uses pass by object reference.
Variable holds reference to objects
when passing arguments. References to these objects are passed.
Mutable objects like 📍 list 📍 dictionaries can be modified within the whereas immutable 📍 📍 objects like strings cannot.
So Python doesn't strictly use pass by value or passed by difference. It has its unique approach./media:description>
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yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>From #chemicalengineering to #datascience | Watch Aakash interview Rishabh, Data Scientist, Uber/title>
link rel="alternate" href="https://www.youtube.com/watch?v=oRhD7j_HtaU"/>
author>
name>Jovian/name>
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published>2023-06-29T15:30:08+00:00/published>
updated>2024-04-14T15:32:35+00:00/updated>
media:group>
media:title>From #chemicalengineering to #datascience | Watch Aakash interview Rishabh, Data Scientist, Uber/media:title>
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media:description>The speaker, who majored in chemical engineering, became interested in data science because they wanted to use their technical ability to optimize pipelines and draw insights for business decisions./media:description>
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id>yt:video:M6bnZfFnXZs/id>
yt:videoId>M6bnZfFnXZs/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>#generativeai is a $100m market | How can you apply GenAI?/title>
link rel="alternate" href="https://www.youtube.com/watch?v=M6bnZfFnXZs"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
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published>2023-06-27T15:30:10+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>#generativeai is a $100m market | How can you apply GenAI?/media:title>
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media:description>Did you know that the global market for Generative AI is expected to reach a hundred billion dollars by 2025?
Here are some of the applications that could lead to this market!
1. First up, we've got content creation.
Generative AI can write news articles, social media posts, and even entire novels.
2. Next, let's talk virtual assistants and chatbots.
With Generative AI, we can create virtual assistants and chatbots that can talk to us just like a real person. It's like having a personal assistant in your pocket.
3. If you're a gamer, you'll love this one.
Generative AI can generate game content like levels, characters, and create personalized gameplay experiences based on your behavior.
4. Art and design are another area
where Generative AI shines. It can generate beautiful artwork and create custom designs based on preferences.
5. Lastly, Generative AI
can help us revolutionize healthcare. It can analyze medical images, develop personalized treatment plan based on the patient data.
Subscribe to our channel for more such content!/media:description>
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yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Exploring Relational vs Non Relational Databases | #sql #datascience #machinelearning/title>
link rel="alternate" href="https://www.youtube.com/watch?v=KEqvAMZQ_PI"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
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published>2023-06-26T15:30:07+00:00/published>
updated>2024-04-14T15:32:35+00:00/updated>
media:group>
media:title>Exploring Relational vs Non Relational Databases | #sql #datascience #machinelearning/media:title>
media:content url="https://www.youtube.com/v/KEqvAMZQ_PI?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
media:thumbnail url="https://i4.ytimg.com/vi/KEqvAMZQ_PI/hqdefault.jpg" width="480" height="360"/>
media:description>A database is a piece of software that stores all the data for an application, and it can be relational or non-relational, with relational databases allowing for efficient querying and combining of tables.
Full Video: https://www.youtube.com/watch?v=V95IT5jJOjU/media:description>
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media:starRating count="36" average="5.00" min="1" max="5"/>
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yt:videoId>RV_MihEQ4BA/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Building Generative AI Apps with Python & Streamlit/title>
link rel="alternate" href="https://www.youtube.com/watch?v=RV_MihEQ4BA"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
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published>2023-06-26T04:02:19+00:00/published>
updated>2024-02-29T04:18:42+00:00/updated>
media:group>
media:title>Building Generative AI Apps with Python & Streamlit/media:title>
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id>yt:video:ZXXcb4ELVd0/id>
yt:videoId>ZXXcb4ELVd0/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Understanding Foreign Keys: Connecting Tables in #sql #database #datascience/title>
link rel="alternate" href="https://www.youtube.com/watch?v=ZXXcb4ELVd0"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
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published>2023-06-24T14:30:09+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>Understanding Foreign Keys: Connecting Tables in #sql #database #datascience/media:title>
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media:thumbnail url="https://i3.ytimg.com/vi/ZXXcb4ELVd0/hqdefault.jpg" width="480" height="360"/>
media:description>Foreign keys are used to represent relationships between different tables, such as an orders table having a primary key for order ID and foreign keys for the corresponding user and product tables, allowing for a three-way join to retrieve all relevant data.
Watch the full video here: https://www.youtube.com/watch?v=V95IT5jJOjU/media:description>
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id>yt:video:3dZ9m6bJonM/id>
yt:videoId>3dZ9m6bJonM/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Workshop Building Generative AI Apps with React and useLLM - June 24 2023/title>
link rel="alternate" href="https://www.youtube.com/watch?v=3dZ9m6bJonM"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
/author>
published>2023-06-24T13:08:42+00:00/published>
updated>2024-02-19T12:27:00+00:00/updated>
media:group>
media:title>Workshop Building Generative AI Apps with React and useLLM - June 24 2023/media:title>
media:content url="https://www.youtube.com/v/3dZ9m6bJonM?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
media:thumbnail url="https://i4.ytimg.com/vi/3dZ9m6bJonM/hqdefault.jpg" width="480" height="360"/>
media:description>Directions and steps: https://paper.dropbox.com/doc/Generative-AI-Workshop--B60_mI8IvZg2dJGXUniWxm3kAg-2vcXrvet7uUhfLWiTOae0
Documentation and examples: https://usellm.org
Please excuse the bad audio, this video was recorded as a live event!/media:description>
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entry>
id>yt:video:s13epHhJeEM/id>
yt:videoId>s13epHhJeEM/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>#opensource Large Language Models you should use to build!/title>
link rel="alternate" href="https://www.youtube.com/watch?v=s13epHhJeEM"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
/author>
published>2023-06-22T15:30:11+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>#opensource Large Language Models you should use to build!/media:title>
media:content url="https://www.youtube.com/v/s13epHhJeEM?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
media:thumbnail url="https://i4.ytimg.com/vi/s13epHhJeEM/hqdefault.jpg" width="480" height="360"/>
media:description>Want to build an NLP project and don’t know where to begin from.
You need to try out these language models, which are completely free and open source and powerful enough to build cool things like a chat bot or a translator.
1. GPT 2: developed by OpenAI GPT 2 is capable of generating logical and diverse text, making it ideal for tasks such as language translation, text summarization, and even creative writing.
2. BERT: a powerful LLM developed by Google. BERT is designed to understand context and subtle differences of languages, making it suitable for tasks like sentiment analysis.
3. LLAMA: Introduced by meta. This large language model, despite being 10 times smaller, outperformed GPT 3 on tasks like text generation and language translation.
Let us know if you try out these open source LLMs/media:description>
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id>yt:video:F72r0Jtb4M0/id>
yt:videoId>F72r0Jtb4M0/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>Mastering #sql : Essential for #data #management #ai #frontenddeveloper/title>
link rel="alternate" href="https://www.youtube.com/watch?v=F72r0Jtb4M0"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
/author>
published>2023-06-21T15:30:11+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>Mastering #sql : Essential for #data #management #ai #frontenddeveloper/media:title>
media:content url="https://www.youtube.com/v/F72r0Jtb4M0?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
media:thumbnail url="https://i3.ytimg.com/vi/F72r0Jtb4M0/hqdefault.jpg" width="480" height="360"/>
media:description>SQL is important for setting up data models and retrieving data, making it an essential skill to have.
Full Podcast here: https://www.youtube.com/watch?v=V95IT5jJOjU/media:description>
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media:starRating count="40" average="5.00" min="1" max="5"/>
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entry>
id>yt:video:CVWwK1Cx7BM/id>
yt:videoId>CVWwK1Cx7BM/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>E for Explainable AI/title>
link rel="alternate" href="https://www.youtube.com/watch?v=CVWwK1Cx7BM"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
/author>
published>2023-06-19T15:00:11+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>E for Explainable AI/media:title>
media:content url="https://www.youtube.com/v/CVWwK1Cx7BM?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
media:thumbnail url="https://i4.ytimg.com/vi/CVWwK1Cx7BM/hqdefault.jpg" width="480" height="360"/>
media:description>📍 Imagine
having a one-on-one discussion
📍 with your favorite
machine learning model.
Well, that's E for Explainable AI or XAI.
In short,
XAI is like opening up the
black box of AI.
It's all about making AI
models more understandable
so we can trust and
validate their decisions.
It also makes it easier
to spot biases and
ensure that AI is fair to
everyone,
📍 like a superhero fighting for justice
With XAI, doctors can understand
why an AI model recommends
a certain treatment,
and banks can see the
reason behind credit
score predictions.
It's like giving the
AI the power of communication.
Some popular ways to make
AI more explainable include
LIME, Shap and
Partial Dependence plots.
These tools help us speak
inside the AI's mind and understand
the logic behind its decisions,
just like a detective solving
a mystery, and that's how we
can trust AI to make life-changing decisions./media:description>
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media:starRating count="60" average="5.00" min="1" max="5"/>
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entry>
id>yt:video:2RU6AoDAZk8/id>
yt:videoId>2RU6AoDAZk8/yt:videoId>
yt:channelId>UCmKaoNn0OvxVAe7f_8sXYNQ/yt:channelId>
title>D for Deep Learning/title>
link rel="alternate" href="https://www.youtube.com/watch?v=2RU6AoDAZk8"/>
author>
name>Jovian/name>
uri>https://www.youtube.com/channel/UCmKaoNn0OvxVAe7f_8sXYNQ/uri>
/author>
published>2023-06-17T13:30:11+00:00/published>
updated>2024-04-14T15:32:36+00:00/updated>
media:group>
media:title>D for Deep Learning/media:title>
media:content url="https://www.youtube.com/v/2RU6AoDAZk8?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
media:thumbnail url="https://i3.ytimg.com/vi/2RU6AoDAZk8/hqdefault.jpg" width="480" height="360"/>
media:description>What if
we could teach computers
to be as smart as 📍 Tony Stark's
Jarvis?
That is the power of
📍 Deep Learning.
📍 Deep learning is how
computers learn to think.
It uses layers of
artificial neurons to
learn and
make decisions
from the information
we give it
Inspired by our own brain
more layers mean it
can learn and understand
more complex stuff
like Tony Stark
upgrading his suit.
Deep learning has
changed the game in areas
like 📍 📍 image recognition,
📍 language understanding,
and
📍 📍 even self-driving cars.
It has its challenges like
needing lots of data or
taking a long time to learn.
But with cool tricks
like dropout,
bash normalization &
data augmentation,
we can help it learn even better.
That's a quick tour of
Deep Learning.
Don't miss a next episode in the
A to Z of AI!
E is for,
well.
You'll have to wait till the next time for that/media:description>
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id>yt:video:0qxFYACytEg/id>
yt:videoId>0qxFYACytEg/yt:videoId>
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title>Can you become a #datascientist without a #cs degree? | Rishabh's Mock Interview with Aakash/title>
link rel="alternate" href="https://www.youtube.com/watch?v=0qxFYACytEg"/>
author>
name>Jovian/name>
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media:title>Can you become a #datascientist without a #cs degree? | Rishabh's Mock Interview with Aakash/media:title>
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media:description>The number of rounds in a data science job interview varies depending on the company and the expectations of the role./media:description>
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title>Deploying ML Models in 60 Minutes using Python, Flask & Render | Step-by-Step Tutorial/title>
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media:title>Deploying ML Models in 60 Minutes using Python, Flask & Render | Step-by-Step Tutorial/media:title>
media:content url="https://www.youtube.com/v/rgr_aCg-338?version=3" type="application/x-shockwave-flash" width="640" height="390"/>
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media:description>Deployment Notebook: https://jovian.com/biraj/deploying-a-machine-learning-model
Source Code: https://github.com/BirajCoder/practice-deployment/tree/main
Model Training Notebook: https://jovian.com/birajde9/email-spam-classifier-naive-bayes
Model Deployment is a critical phase in the machine learning pipeline where a developed model is made available in a production environment, enabling it to generate real-world predictions. The value of machine learning can only be actualized when a model is successfully deployed and integrated into a product or service.
In this workshop, you'll delve into the process of deploying a machine learning model onto a web application using Flask, a leading Python web framework. By the end of the session, you'll have a firm grasp of the deployment process and be well-prepared to deploy your own models.
Timestamps:
00:00 - Introduction
01:57 - Prerequisites and Problem Statement
3:39 - Project Setup on GitHub and Conda
12:02 - Create a Simple Flask Application
18:54 - Creating a Simple Form
23:25 - Sending a POST request
29:50 - Machine Learning Model
31:03 - Running the Model Locally
48:33 - Deploying the Flask Application on Render
56:52 - Creating an API route
1:05:15 - Code Refactoring
1:09:58 - Exercise
1:10:01 - Summary
1:12:20 - Questions
Agenda:
The workshop is organized into distinct segments as follows:
1. Creating the First Web App Using Flask: Kick-start your Flask journey by creating your first web app.
2. Adding Forms and Jinja Template: Learn to add forms to your web app and understand how to use Jinja for efficient template management.
3. Deploying the ML Model Locally: Step-by-step guidance on deploying your pre-trained machine learning model on a local Flask server.
4. Publishing the Web App Online: Once your model is deployed locally, learn the ins and outs of making it accessible online.
5. Improving the Page Layout Using CSS: Lastly, discover how to use CSS to enhance the look and feel of your webpage.
Speaker: Biraj De
The workshop's speaker is a B.Tech grad from Kolkata, skilled in programming and data science. He started coding 7 years ago in languages like C, Java, Python, and JavaScript. Three years ago, he shifted to Data Science, after improving his problem-solving skills through competitions on platforms like Codechef, Hackerrank, and Leetcode. He attended multiple ML and Coding workshops/hackathons Now, for two years, he's been a dedicated data science teacher, guiding others in the exciting fields of Machine Learning and Data Science
#ml #machinelearning #modeldeployment #deployment #python #flask #python3 #render #production #email #spam #classification/media:description>
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Jovian
01.08.2023 19:27:12
01.01.1970 01:00:00
04.05.2023 04:45:23 5 60
28.07.2024 08:26:22
01.01.1970 01:00:00
04.05.2023 04:45:23 5 62
1:: Jovian's Batch of November 2023 Graduation Day!
01.01.1970 01:00:00 01.11.2023 14:30:10 Join us for Jovian’s Data Science Bootcamp Graduation Day
Over the past eight months, participants of the program have spent 600+ hours learning data science & machine learning and building real-world projects. Join us to congratulate the graduates and celebrate the fantastic work done by the Jovian community.
List of Speakers
00:00:00 - Introduction
00:00:21 - Pragya Khatri
00:02:51 - Manjunath Reddy
00:05:38 - Haridev S
00:08:33 - Kris Holmquist
00:11:16 - Prabhakar Rawat
00:14:29 - Nnaemeka Hillary Onah
00:17:17 - Saurabh Pati Tripathi
00:20:23 - Anshika Nigam
00:23:09 - Sarthak Srivastava
00:26:02 - Mahima Srivastava
00:29:40 - Chinmaye Chinnappa H E
00:32:36 - Thank you
2:: Jovian's Batch of September 2023 Graduation Day!
01.01.1970 01:00:00 11.09.2023 14:30:10 Join us for Jovian’s Data Science Bootcamp Graduation Day
Over the past eight months, participants of the program have spent 600+ hours learning data science & machine learning and building real-world projects. Join us to congratulate the graduates and celebrate the fantastic work done by the Jovian community.
List of Speakers
00:00:00 - Introduction
00:00:23 - Suraj D
00:03:07 - Joyesh Meshram
00:05:43 - Anjali Ramesh
00:09:40 - Bhavya Bajaj
00:12:22 - Ahlenoor Khan
00:15:02 - Tuan Nguyen
00:17:43 - Sneha Bajaj
00:20:37 - Abhishek Bhardwaj
00:23:37 - Aehtajaz Ahmed
00:26:37 - Thank you
3:: Difference between Pass by Value, Pass by Reference | #python
01.01.1970 01:00:00 30.06.2023 14:30:08 📍 📍 Did you know the way you pass arguments to a function can make a huge difference in your code? Let's explore. Pass by value, pass by reference, and how Python handle these concepts.
📍 When you pass an argument by value, a copy of the value is sent to the function.
Any changes made within the function doesn't affect the original variable.
When you pass an argument by reference,
you are passing the memory address of the variable.
Changes made within the function directly affect the original variable
now these concepts are very commonly used in languages like 📍 C, 📍 C plus plus 📍 PHP, et cetera, but
python uses pass by object reference.
Variable holds reference to objects
when passing arguments. References to these objects are passed.
Mutable objects like 📍 list 📍 dictionaries can be modified within the whereas immutable 📍 📍 objects like strings cannot.
So Python doesn't strictly use pass by value or passed by difference. It has its unique approach.
4:: From #chemicalengineering to #datascience | Watch Aakash interview Rishabh, Data Scientist, Uber
01.01.1970 01:00:00 29.06.2023 15:30:08 The speaker, who majored in chemical engineering, became interested in data science because they wanted to use their technical ability to optimize pipelines and draw insights for business decisions.
5:: #generativeai is a $100m market | How can you apply GenAI?
01.01.1970 01:00:00 27.06.2023 15:30:10 Did you know that the global market for Generative AI is expected to reach a hundred billion dollars by 2025?
Here are some of the applications that could lead to this market!
1. First up, we've got content creation.
Generative AI can write news articles, social media posts, and even entire novels.
2. Next, let's talk virtual assistants and chatbots.
With Generative AI, we can create virtual assistants and chatbots that can talk to us just like a real person. It's like having a personal assistant in your pocket.
3. If you're a gamer, you'll love this one.
Generative AI can generate game content like levels, characters, and create personalized gameplay experiences based on your behavior.
4. Art and design are another area
where Generative AI shines. It can generate beautiful artwork and create custom designs based on preferences.
5. Lastly, Generative AI
can help us revolutionize healthcare. It can analyze medical images, develop personalized treatment plan based on the patient data.
Subscribe to our channel for more such content!
6:: Exploring Relational vs Non Relational Databases | #sql #datascience #machinelearning
01.01.1970 01:00:00 26.06.2023 15:30:07 A database is a piece of software that stores all the data for an application, and it can be relational or non-relational, with relational databases allowing for efficient querying and combining of tables.
Full Video: https://www.youtube.com/watch?v=V95IT5jJOjU
7:: Building Generative AI Apps with Python & Streamlit
01.01.1970 01:00:00 26.06.2023 04:02:19
8:: Understanding Foreign Keys: Connecting Tables in #sql #database #datascience
01.01.1970 01:00:00 24.06.2023 14:30:09 Foreign keys are used to represent relationships between different tables, such as an orders table having a primary key for order ID and foreign keys for the corresponding user and product tables, allowing for a three-way join to retrieve all relevant data.
Watch the full video here: https://www.youtube.com/watch?v=V95IT5jJOjU
9:: Workshop Building Generative AI Apps with React and useLLM - June 24 2023
01.01.1970 01:00:00 24.06.2023 13:08:42 Directions and steps: https://paper.dropbox.com/doc/Generative-AI-Workshop--B60_mI8IvZg2dJGXUniWxm3kAg-2vcXrvet7uUhfLWiTOae0
Documentation and examples: https://usellm.org
Please excuse the bad audio, this video was recorded as a live event!
10:: #opensource Large Language Models you should use to build!
01.01.1970 01:00:00 22.06.2023 15:30:11 Want to build an NLP project and don’t know where to begin from.
You need to try out these language models, which are completely free and open source and powerful enough to build cool things like a chat bot or a translator.
1. GPT 2: developed by OpenAI GPT 2 is capable of generating logical and diverse text, making it ideal for tasks such as language translation, text summarization, and even creative writing.
2. BERT: a powerful LLM developed by Google. BERT is designed to understand context and subtle differences of languages, making it suitable for tasks like sentiment analysis.
3. LLAMA: Introduced by meta. This large language model, despite being 10 times smaller, outperformed GPT 3 on tasks like text generation and language translation.
Let us know if you try out these open source LLMs
11:: Mastering #sql : Essential for #data #management #ai #frontenddeveloper
01.01.1970 01:00:00 21.06.2023 15:30:11 SQL is important for setting up data models and retrieving data, making it an essential skill to have.
Full Podcast here: https://www.youtube.com/watch?v=V95IT5jJOjU
12:: Understanding #sql | What is SQL? #data
01.01.1970 01:00:00 20.06.2023 15:30:12 SQL is a language used to efficiently manage and retrieve data from tables within relational databases, which are used to store user data in applications such as e-commerce.
Watch the full video here: https://www.youtube.com/watch?v=V95IT5jJOjU
13:: E for Explainable AI
01.01.1970 01:00:00 19.06.2023 15:00:11 📍 Imagine
having a one-on-one discussion
📍 with your favorite
machine learning model.
Well, that's E for Explainable AI or XAI.
In short,
XAI is like opening up the
black box of AI.
It's all about making AI
models more understandable
so we can trust and
validate their decisions.
It also makes it easier
to spot biases and
ensure that AI is fair to
everyone,
📍 like a superhero fighting for justice
With XAI, doctors can understand
why an AI model recommends
a certain treatment,
and banks can see the
reason behind credit
score predictions.
It's like giving the
AI the power of communication.
Some popular ways to make
AI more explainable include
LIME, Shap and
Partial Dependence plots.
These tools help us speak
inside the AI's mind and understand
the logic behind its decisions,
just like a detective solving
a mystery, and that's how we
can trust AI to make life-changing decisions.
14:: D for Deep Learning
01.01.1970 01:00:00 17.06.2023 13:30:11 What if
we could teach computers
to be as smart as 📍 Tony Stark's
Jarvis?
That is the power of
📍 Deep Learning.
📍 Deep learning is how
computers learn to think.
It uses layers of
artificial neurons to
learn and
make decisions
from the information
we give it
Inspired by our own brain
more layers mean it
can learn and understand
more complex stuff
like Tony Stark
upgrading his suit.
Deep learning has
changed the game in areas
like 📍 📍 image recognition,
📍 language understanding,
and
📍 📍 even self-driving cars.
It has its challenges like
needing lots of data or
taking a long time to learn.
But with cool tricks
like dropout,
bash normalization &
data augmentation,
we can help it learn even better.
That's a quick tour of
Deep Learning.
Don't miss a next episode in the
A to Z of AI!
E is for,
well.
You'll have to wait till the next time for that
15:: Can you become a #datascientist without a #cs degree? | Rishabh's Mock Interview with Aakash
01.01.1970 01:00:00 15.06.2023 16:30:09 The number of rounds in a data science job interview varies depending on the company and the expectations of the role.
16:: Deploying ML Models in 60 Minutes using Python, Flask & Render | Step-by-Step Tutorial
01.01.1970 01:00:00 15.06.2023 03:15:50 Deployment Notebook: https://jovian.com/biraj/deploying-a-machine-learning-model
Source Code: https://github.com/BirajCoder/practice-deployment/tree/main
Model Training Notebook: https://jovian.com/birajde9/email-spam-classifier-naive-bayes
Model Deployment is a critical phase in the machine learning pipeline where a developed model is made available in a production environment, enabling it to generate real-world predictions. The value of machine learning can only be actualized when a model is successfully deployed and integrated into a product or service.
In this workshop, you'll delve into the process of deploying a machine learning model onto a web application using Flask, a leading Python web framework. By the end of the session, you'll have a firm grasp of the deployment process and be well-prepared to deploy your own models.
Timestamps:
00:00 - Introduction
01:57 - Prerequisites and Problem Statement
3:39 - Project Setup on GitHub and Conda
12:02 - Create a Simple Flask Application
18:54 - Creating a Simple Form
23:25 - Sending a POST request
29:50 - Machine Learning Model
31:03 - Running the Model Locally
48:33 - Deploying the Flask Application on Render
56:52 - Creating an API route
1:05:15 - Code Refactoring
1:09:58 - Exercise
1:10:01 - Summary
1:12:20 - Questions
Agenda:
The workshop is organized into distinct segments as follows:
1. Creating the First Web App Using Flask: Kick-start your Flask journey by creating your first web app.
2. Adding Forms and Jinja Template: Learn to add forms to your web app and understand how to use Jinja for efficient template management.
3. Deploying the ML Model Locally: Step-by-step guidance on deploying your pre-trained machine learning model on a local Flask server.
4. Publishing the Web App Online: Once your model is deployed locally, learn the ins and outs of making it accessible online.
5. Improving the Page Layout Using CSS: Lastly, discover how to use CSS to enhance the look and feel of your webpage.
Speaker: Biraj De
The workshop's speaker is a B.Tech grad from Kolkata, skilled in programming and data science. He started coding 7 years ago in languages like C, Java, Python, and JavaScript. Three years ago, he shifted to Data Science, after improving his problem-solving skills through competitions on platforms like Codechef, Hackerrank, and Leetcode. He attended multiple ML and Coding workshops/hackathons Now, for two years, he's been a dedicated data science teacher, guiding others in the exciting fields of Machine Learning and Data Science
#ml #machinelearning #modeldeployment #deployment #python #flask #python3 #render #production #email #spam #classification
17:: Boosting #sql Skills for #datascience Interviews
01.01.1970 01:00:00 14.06.2023 14:30:10 To showcase good SQL skills on a resume for an entry-level data scientist role, it is important to practice and showcase projects that demonstrate clear understanding of the basics, as the first round of interviews often involves a full-fledged SQL round.
18:: 5 FREE AI Image Generation Tools to try Today! #ai #generativeart #artificialintelligence
01.01.1970 01:00:00 27.04.2023 15:30:03
19:: Episode 5 - Jobot Enters the Matrix | How to Build an AI
01.01.1970 01:00:00 27.04.2023 03:10:40
20:: Practice for your next interview with Jobot! #ai #chatgpt #machinelearning
01.01.1970 01:00:00 26.04.2023 15:30:00
21:: Why AI can’t generate hands - PT.2 | #ai #jovian #programming #chatgpt #machinelearning #diffusion
01.01.1970 01:00:00 25.04.2023 15:30:03
22:: Episode 4 - Jobot Makes New Friends | How to Build an AI
01.01.1970 01:00:00 25.04.2023 02:27:03
23:: Why AI can’t generate hands? Pt1 #programming #ai #chatgpt
01.01.1970 01:00:00 24.04.2023 15:30:06
24:: Spotify's SQL Question & Answer | Crack ANY Interview with this 3 Step Approach
01.01.1970 01:00:00 23.04.2023 13:30:26
25:: Episode 3 - Jobot Learns New Tricks | How to Build an AI
01.01.1970 01:00:00 22.04.2023 02:55:24
26:: Episode 2 - Jobot Meets the World | How to Build an AI
01.01.1970 01:00:00 20.04.2023 03:26:42
27:: Is your Job at Risk Due to AI? #ai #programming #chatgpt
01.01.1970 01:00:00 19.04.2023 15:30:12
28:: May 2023 Batch Graduation Day - Jovian Data Science Bootcamp
01.01.1970 01:00:00 19.04.2023 06:08:53
29:: The Secret Behind AI-Generated Images
01.01.1970 01:00:00 18.04.2023 15:30:11
30:: Power BI vs Tableau | Which One is For You? #programming #powerbi #tableau #datascience #project
01.01.1970 01:00:00 18.04.2023 15:30:10
31:: How Krithika built a Successful Career marrying Data & Business | ONLY Interview Tips you need
01.01.1970 01:00:00 17.04.2023 15:30:00
32:: Episode 1 - First Contact with Jobot | How to Build an AI
01.01.1970 01:00:00 17.04.2023 03:27:49
33:: 30 March 2023
01.01.1970 01:00:00 30.03.2023 15:30:09
34:: Plotting Geospatial data with Python - Part 3 - Tile Styles in Folium
01.01.1970 01:00:00 30.03.2023 13:30:21
35:: Did you meet Jobot yet? #jovian #artificialintelligence
01.01.1970 01:00:00 29.03.2023 17:43:10
36:: What is Precision in Machine Learning?
01.01.1970 01:00:00 28.03.2023 15:30:10
37:: Learn 10X Faster with Jobot! | Jovian's ChatGPT-powered bot
01.01.1970 01:00:00 27.03.2023 15:30:10
38:: This Week's AI Roundup Part 2: ChatGPT, Unity, Canva, and Exciting AI Innovations!
01.01.1970 01:00:00 26.03.2023 17:00:08
39:: This Week's AI Roundup Part 1: BARD, NVIDIA, Adobe, Runway and More!
01.01.1970 01:00:00 26.03.2023 15:30:11
40:: Meta's SQL Interview Question & Answer | Three-Step Approach
01.01.1970 01:00:00 25.03.2023 13:30:08
41:: Is your Job at Risk? The future of careers with AI
01.01.1970 01:00:00 24.03.2023 15:30:12
42:: Meet Jobot! Jovian’s ChatGPT powered boy #jovian #artificialintelligence #chatgpt
01.01.1970 01:00:00 23.03.2023 15:07:48
43:: The Samsung Space Zoom Controversy (Part 2) | Samsung's Response
01.01.1970 01:00:00 22.03.2023 15:30:13
44:: Plotting Geospatial data with Python - Part 2 - Adding Markers on Folium Maps
01.01.1970 01:00:00 22.03.2023 13:30:02
45:: What is Accuracy in Machine Learning?
01.01.1970 01:00:00 21.03.2023 15:30:16
46:: The Samsung Space Zoom Controversy (Part 1) | Are Moon Photos Real or Fake
01.01.1970 01:00:00 20.03.2023 15:30:00
47:: Applications of ControlNet with Stable Diffusion - Kartik Godawat, Founder, DeepKlarity
01.01.1970 01:00:00 20.03.2023 13:30:04
48:: What is Root Mean Squared Error (RMSE) in Machine Learning?
01.01.1970 01:00:00 14.02.2023 11:30:14
49:: The Impact of ChatGPT & the smartest way to Learn while you Earn | Samridh Amla, Microsoft
01.01.1970 01:00:00 13.02.2023 07:21:38
50:: Insights from Explainable AI | Join us LIVE, 16 Feb - 7 PM IST
01.01.1970 01:00:00 11.02.2023 06:30:07
51:: How Can Machine Learning Help During Earthquakes?
01.01.1970 01:00:00 10.02.2023 15:30:08
52:: 5 ML Project Ideas In Healthcare Sector For Your Resume
01.01.1970 01:00:00 10.02.2023 11:30:13
53:: The Art of Standing Out in Tech: Building Unique Projects | Samridh Amla, Microsoft
01.01.1970 01:00:00 10.02.2023 06:18:00
54:: Learn Programming Languages of the Present or Future? | Samridh Amla, Microsoft
01.01.1970 01:00:00 09.02.2023 04:50:35
55:: Solving a LeetCode problem step by step | 20. Valid Paranthesis
01.01.1970 01:00:00 08.02.2023 11:30:03
56:: EdTech Platform System Design & Software Architecture Case Study | Jovian
01.01.1970 01:00:00 07.02.2023 15:23:57
57:: What Challenges did you face while breaking into Software Development? | Samridh Amla, Microsoft
01.01.1970 01:00:00 07.02.2023 11:30:19
58:: What are Evaluation Metrics in Machine Learning?
01.01.1970 01:00:00 07.02.2023 11:30:15
59:: Lets Talk Data Science E3: Rishabh Gupta, Uber
01.01.1970 01:00:00 06.02.2023 15:42:36
60:: Side projects that got you Hooked on Software Engineering | Samridh Amla Microsoft
01.01.1970 01:00:00 06.02.2023 15:19:42
61:: 5 ML Projects Ideas In Finance For Your Resume
01.01.1970 01:00:00 03.02.2023 12:00:28
62:: Must-Have Projects for your Data Science & ML Portfolio
01.01.1970 01:00:00 08.09.2022 00:00:00