I know this maybe a silly question but at 21:47 how do I know that the "item_id" is going to be "7"?

great🧠

Please tell me you revoked that key!

thank you for making this videos

Is these videos are AI generated?

Thank you professor for this great mastercourse

Thank you professor for this nice course

This was quite amazing. It covered quite a lot in that one hour including various agentic workflows, reflection and tool calling. Of course it was just a starter, but I kept taking notes to search for more in depth materials or code on autogen.

00:04 Supervised learning is the process of filling a straight line to your data using a linear regression model. 01:16 Using a linear regression model to estimate the price of a house based on its size. 02:20 Linear regression is a type of supervised learning model used for regression problems. 03:33 Classification involves a small number of possible outputs, while regression has infinitely many possible numbers as outputs. 04:45 Understanding data plot and notation in machine learning. 06:11 The input data used to train the model is called a training set. 07:41 The dataset has 47 rows, each representing a different training example. 09:13 An index I refers to a specific row in the table Crafted by Merlin AI.

You make a great app as a like teacher when the topic is not understandable we send them a picture of this topic she explain us on this picture and further explain

Excellent!

Thank you so much dear Andrew, I watched all the sessions and it was really informative, just need to start deploy some models in practice :)

👏👏

Your content is falling off

59:00

This has become mostly a platform for startups advertising their products, right?

55:57

44:00

why do we assume that the parameters for the layers are the same ?

Awesome course. So much better and educational content than loads of random content from the web. I wasted time until I found this course. Now things looks clearer and I think I am ready to explore my use case. You made my day!

Leaky ReLU (Rectified Linear Unit) and ReLU are both popular activation functions in Deep Learning, but with a key difference in how they handle negative inputs. **ReLU (Rectified Linear Unit):** * **Function:** ReLU simply sets any negative input to zero, and keeps positive inputs unchanged. Imagine a switch that turns on (outputs a value) only for positive inputs and stays off (outputs zero) for negative inputs. * **Advantage:** ReLU is computationally efficient and helps prevent vanishing gradients, a problem that can hinder training in deep neural networks. * **Disadvantage:** ReLU suffers from a problem called "dying ReLU." If a neuron consistently receives negative inputs and its weights aren't adjusted properly, it can become permanently inactive (stuck at zero output) and never learn. **Leaky ReLU:** * **Function:** Leaky ReLU addresses the "dying ReLU" problem. It acts like a regular ReLU for positive inputs, but for negative inputs, it allows a small, non-zero gradient to flow through. This small gradient helps keep the neuron slightly active and allows it to potentially learn from negative data points. * **Advantage:** Leaky ReLU overcomes the "dying ReLU" issue and can learn from both positive and negative data. * **Disadvantage:** Leaky ReLU introduces an additional parameter, the slope for the negative input region. Choosing the optimal slope can require some experimentation. It's also slightly less computationally efficient than ReLU due to the extra calculation for the negative slope.

32:40

Indians assemble

20:18

11:39

Your vids are really helping me man and i've been in digital marketing for 13 years, generated hundreds of millions! so good! i'm inspired to keep actually releasing stuff!

I had no intent of watching upto this point but Im loving it. Thanks for your and your team’s hard work!

where is the lab link??????????????????????????????

cat meow, dog woof

Is this course still relevant today after a year has passed?

Where is the Lab file?!!! I couldn't find it!!!!

3:42 random Andrew Ng flex on chinese logographs writing skills

This course is not running properly on the website just like RLHF, please help. I really want to take this course

thats fire

I'm so excited about this course. Andrew Ng is da GOAT!

Andrew is doing a fab job. I have foolowing him for quite a while and he piqued my interest in long before chatgpt. I am building my foundations in python and C before I pick AI, honestly which area in AI should one pick is hard one in itself

Very valuable course for me and AI engineers by Senior Data Scientist.....Always doing great job by Andrew and kudos to the tech teams.....

How do I enroll

Second/Third ? :)

I have a gradient descent with momentum optimizing parameters for a differential equation. There are 5 parameters. It is impossible to know the shape of the ovals in 5 dimensions. It is also real and not perfect data. Determining alpha and beta is a trick and often takes trial and error. I wish these videos would use the same symbols. There is no consistency. Just about any minimize routine is faster than gradient descent for small number of parameters.

explained extremely well!

Hi! To all those people who are searching for the optional lab codes, you can ask chatgpt with detail requirements addressing the course name etc. and it will give you all the codes. Since you have been able to come this far, you will be able to find the code too. Happy coding.

Thank you very much.

Awesome! Thank you

First 😂

Not complete course found for free

Why do we need multiple-agents ? Can't a crew of Agents be replaced by ONE very long prompt used for 1 "agent" ? You can concatenate the goals of the agents into 1 single prompt, so that GenAI can do the steps sequentially.

This is awesome! Thank you so much to both of you for this 🔥

Bless you both. The miracles you provide are underrated. 🙏