🔴 To learn Data Analytics & Python Course online with regular LIVE CLASSES, enroll now: www.wscubetech.com/landing-pages/online-data-analytics-course.html?TH-cam&April2024_22&RV
Machine learning Part 2 chahiye 😢 please please please aap upload kariyega agar thousand comments na bhi hue to . Thanks for providing informative videos. Thanks A lote.❤
Thank once again for your efforts to make young guys skill ful.Kindly make videos about tensorflow and keras ,make some projects using some dataset,How to get job n ML,DL.If you need any Subtitles services I will do it with less price.
00:02 Deep learning teaches computers to learn and recognize patterns. 02:42 Deep learning is a subpart of machine learning 06:52 Introduction to Neural Networks in Deep Learning 08:45 Deep learning is used in real-world applications 12:30 Understanding the working of neurons and neural networks 14:19 Understanding the data collection process inside cells. 18:21 Understanding single layer perceptron and multi-layer neural networks 19:56 Introduction to neural networks 23:52 Weightage in managing data and output 25:40 Understanding activation functions in deep learning 29:18 Single Layer Perceptron is limited for complex data handling 31:06 Introduction to Machine Learning Algorithms 34:15 Data is separated into input and output for model testing. 35:51 Building and evaluating a Deep Learning model. 39:02 Introduction to Single-Layer Perceptron 40:34 Introduction to Multilayer Perceptron 43:46 Understanding weightage and bias computation in neural networks 45:15 Explaining the structure of neural networks 48:32 Understanding the concept of multilayer neural networks 50:11 Understanding the activation functions in Multi Layer Perceptron 53:23 Understanding weightage and bias in neural networks 55:02 Explanation of hidden layers and activation functions 58:13 Gradient descent minimizes loss 59:55 Backward propagation and weightage update 1:03:09 Understanding different loss functions and back propagation in deep learning 1:04:44 Explaining Mean Square Loss and Updating Parameters 1:08:22 Importance of learning rate in Deep Learning 1:10:03 Introduction to Single Layer Perceptron 1:13:06 Calculating values using equations in Deep Learning 1:15:00 Backward propagation and gradient descent 1:18:18 Understanding activation functions and their role in non-linear data 1:19:56 The activation function 'linear' is discussed. 1:23:19 Different activation functions in deep learning 1:25:01 Understanding neural network outputs 1:28:22 Understanding loss function basics in deep learning 1:30:15 The algorithm and parameters of neural networks 1:33:38 Understanding the difference between loss and cost functions 1:35:17 Understanding various loss functions in neural networks 1:38:58 Understanding Mean Squared Error in Deep Learning 1:40:36 Understanding modulus and its impact on value 1:43:36 Explanation of Huber Loss in Deep Learning 1:45:12 Log loss formula usage for binary classification 1:48:12 Explanation of one hot encoding 1:49:43 Understanding one-hot encoding and label encoding 1:53:07 Understanding global and local minima in deep learning 1:54:44 Understanding the importance of learning rates in deep learning optimization 1:58:03 Understanding different types of optimizers in Deep Learning 1:59:46 Practical application of multi layer perceptron in analyzing bank customer data 2:03:05 Data Scaling Process Overview 2:04:42 Importance of data scaling in Deep Learning 2:07:45 Setting up the neural network model with activation functions and optimizers 2:09:20 Splitting data for training and testing 2:12:32 Processing and analyzing data in different formats 2:13:51 Performing PRD and checking model accuracy 2:16:55 Analyzing model performance on new data 2:18:28 Training and evaluating the deep learning model. 2:21:42 Optimizing Neural Network for Model Accuracy 2:23:13 Choose the best optimizer and tune hyperparameters for improved model accuracy. 2:26:31 Understanding Hyperparameter Tuning and Overfitting in Neural Networks 2:28:13 Understanding model accuracy and overfitting 2:31:28 Understanding overfitting in Deep Learning 2:33:02 Building and evaluating a deep learning model using TensorFlow 2:35:59 Identifying and addressing overfitting in model training for improved accuracy 2:37:30 Concept of Early Stopping in Deep Learning 2:40:26 Understanding the importance of accuracy in deep learning training and testing 2:41:56 Understanding the process of determining accuracy in training and testing 2:45:04 Understanding callbacks, early stopping, and regularization in deep learning models 2:46:43 Applying L2 regularization in deep learning 2:49:48 Importance of Hyper Parameter Tuning 2:51:47 Importance of proper normalization and activation functions in deep learning Crafted by Merlin AI.
I appreciate the effort you've put into creating these valuable resources. Your dedication to helping others learn coding, machine learning, and deep learning is truly inspiring. Keep up the fantastic work!❤
The differentiation in Gradient Descent is wrong. First of all, it involves Partial Differentiation. Moreover, The derivative would not have any term of higher power. It will have only Linear degree terms.
I am from Pakistan all team is very intelligent and I am watching your videos course and tutorial from 2023 This TH-cam channel is change my life Inshallah
thank you so much for this beautifull deep learning course after machine learning i m lookiing for a deep learning course and you guys did it thank so much for this course @wscubetech bus sir iske baad aap GenAI ka full course le aaiye aap sabhi ki asim krapa hogi
Dear team ham sab Kee aik request he apse, takreeban hum sab ko collage university me Andrew ng style me paraya jata he to please Jis tarah Andrew karwata he please ap b Andrew jese slides Kee Tarah karwao
![The ONLY Data Science & AI Roadmap You NEED [Step-by-Step Guide]](http://i.ytimg.com/vi/G_yaHg-PQaI/mqdefault.jpg)
![The ONLY Data Science & AI Roadmap You NEED [Step-by-Step Guide]](/img/tr.png)
🔴 To learn Data Analytics & Python Course online with regular LIVE CLASSES, enroll now: www.wscubetech.com/landing-pages/online-data-analytics-course.html?TH-cam&April2024_22&RV
Vote for Machine Learning Part 2 👉👉👉
Machine learning Part 2 chahiye 😢 please please please aap upload kariyega agar thousand comments na bhi hue to . Thanks for providing informative videos. Thanks A lote.❤
Please part2 ML
It's very need.
Please provide part 2 for machine learning
Learning from you is incredibly amazing. extremely beneficial to everyone.
Thank once again for your efforts to make young guys skill ful.Kindly make videos about tensorflow and keras ,make some projects using some dataset,How to get job n ML,DL.If you need any Subtitles services I will do it with less price.
Very well explanations and all steps of explanation are connecting dots..
Thank you to all your teams
I'm waiting for machine learning part - 2.
Coming soon!
Very Nice Course Sir
Thanks WscubeTech Team
@wscubetech as I mention in your previous video plz provide dataset that you use in your video it will be more helpful for learners thank you!
I have a request for team ws cube tech please provide digital marketing learning sources with practical knowledge
00:02 Deep learning teaches computers to learn and recognize patterns.
02:42 Deep learning is a subpart of machine learning
06:52 Introduction to Neural Networks in Deep Learning
08:45 Deep learning is used in real-world applications
12:30 Understanding the working of neurons and neural networks
14:19 Understanding the data collection process inside cells.
18:21 Understanding single layer perceptron and multi-layer neural networks
19:56 Introduction to neural networks
23:52 Weightage in managing data and output
25:40 Understanding activation functions in deep learning
29:18 Single Layer Perceptron is limited for complex data handling
31:06 Introduction to Machine Learning Algorithms
34:15 Data is separated into input and output for model testing.
35:51 Building and evaluating a Deep Learning model.
39:02 Introduction to Single-Layer Perceptron
40:34 Introduction to Multilayer Perceptron
43:46 Understanding weightage and bias computation in neural networks
45:15 Explaining the structure of neural networks
48:32 Understanding the concept of multilayer neural networks
50:11 Understanding the activation functions in Multi Layer Perceptron
53:23 Understanding weightage and bias in neural networks
55:02 Explanation of hidden layers and activation functions
58:13 Gradient descent minimizes loss
59:55 Backward propagation and weightage update
1:03:09 Understanding different loss functions and back propagation in deep learning
1:04:44 Explaining Mean Square Loss and Updating Parameters
1:08:22 Importance of learning rate in Deep Learning
1:10:03 Introduction to Single Layer Perceptron
1:13:06 Calculating values using equations in Deep Learning
1:15:00 Backward propagation and gradient descent
1:18:18 Understanding activation functions and their role in non-linear data
1:19:56 The activation function 'linear' is discussed.
1:23:19 Different activation functions in deep learning
1:25:01 Understanding neural network outputs
1:28:22 Understanding loss function basics in deep learning
1:30:15 The algorithm and parameters of neural networks
1:33:38 Understanding the difference between loss and cost functions
1:35:17 Understanding various loss functions in neural networks
1:38:58 Understanding Mean Squared Error in Deep Learning
1:40:36 Understanding modulus and its impact on value
1:43:36 Explanation of Huber Loss in Deep Learning
1:45:12 Log loss formula usage for binary classification
1:48:12 Explanation of one hot encoding
1:49:43 Understanding one-hot encoding and label encoding
1:53:07 Understanding global and local minima in deep learning
1:54:44 Understanding the importance of learning rates in deep learning optimization
1:58:03 Understanding different types of optimizers in Deep Learning
1:59:46 Practical application of multi layer perceptron in analyzing bank customer data
2:03:05 Data Scaling Process Overview
2:04:42 Importance of data scaling in Deep Learning
2:07:45 Setting up the neural network model with activation functions and optimizers
2:09:20 Splitting data for training and testing
2:12:32 Processing and analyzing data in different formats
2:13:51 Performing PRD and checking model accuracy
2:16:55 Analyzing model performance on new data
2:18:28 Training and evaluating the deep learning model.
2:21:42 Optimizing Neural Network for Model Accuracy
2:23:13 Choose the best optimizer and tune hyperparameters for improved model accuracy.
2:26:31 Understanding Hyperparameter Tuning and Overfitting in Neural Networks
2:28:13 Understanding model accuracy and overfitting
2:31:28 Understanding overfitting in Deep Learning
2:33:02 Building and evaluating a deep learning model using TensorFlow
2:35:59 Identifying and addressing overfitting in model training for improved accuracy
2:37:30 Concept of Early Stopping in Deep Learning
2:40:26 Understanding the importance of accuracy in deep learning training and testing
2:41:56 Understanding the process of determining accuracy in training and testing
2:45:04 Understanding callbacks, early stopping, and regularization in deep learning models
2:46:43 Applying L2 regularization in deep learning
2:49:48 Importance of Hyper Parameter Tuning
2:51:47 Importance of proper normalization and activation functions in deep learning
Crafted by Merlin AI.
Great insights and well prepared and presented knowledge.
Do you have English only videos?
Please make the video on the topic "sklearn python library" 😊
Thank you
I appreciate the effort you've put into creating these valuable resources. Your dedication to helping others learn coding, machine learning, and deep learning is truly inspiring. Keep up the fantastic work!❤
It's not complete video...plzz upload deep learning part-2
Thanks a lot for these videos.
Each and every topic is well explained, highly appreciated!!
Kindly upload part2.
Thank you 🎉
Kindly image base dataset pr all ml algorithm and techniques apply kr k upload kry
Excellent explanation ❤❤❤
The differentiation in Gradient Descent is wrong. First of all, it involves Partial Differentiation. Moreover, The derivative would not have any term of higher power. It will have only Linear degree terms.
kindly provide these slides also . this will be quite helpful and time saving for us
I am from Pakistan all team is very intelligent and I am watching your videos course and tutorial from 2023 This TH-cam channel is change my life Inshallah
Time pass krna band kr, ab purh b le... Kci nee poocha kahan se ho, khud hi bakwaas shru krdaitey ho
@TOP_FACTZZ_ bhai Ahmed khan alwazir ko bool rha tha, ab kiyun beech me koodh parag
Jab two chutiya aapas mai mil jaiye tu ye hota hai😂😂😂
But hum sab toh aapke liye kaafir hain😂😂😂😂
bs dikhadi na oqat India walon ..ye he tumhari asliyat. Us Pakistani ne tareef kia kardi tm kud pare apni zalalt dikhane e sham shame m m indian
thankyou for your help
thank you so much for this beautifull deep learning course after machine learning i m lookiing for a deep learning course and you guys did it thank so much for this course @wscubetech bus sir iske baad aap GenAI ka full course le aaiye aap sabhi ki asim krapa hogi
Yes for sure please bring part2
Pls make Part 2 soon 😊
Excellent work
Dear team ham sab Kee aik request he apse, takreeban hum sab ko collage university me Andrew ng style me paraya jata he to please Jis tarah Andrew karwata he please ap b Andrew jese slides Kee Tarah karwao
Hi please bring a course on chat bot ur courses are very helpful and full of information and knowledgeable. Stay blessed team ws cube tech
I have a request Team WS cube tech please make a video on full course of Tabeau for Data analyst
Very important video for beginners, those who are going to swim in Deep learning.
Thanks for effort
nice Sir
Great, I was looking for
Mam or sir ye complete video hai na deep learning ke liya.❤
Reinforcement learning please
can you please share the ppt or note file for the better understanding and revision
Sir ML ka Second Part Kab Aane Wala Hai..?
please bring machine Learning part 2
Gradient descent formula seems to be different. Is this me only or its actually wrong?
Please machine learning part 2
Sir provide machine learning part 3
great video
keep it up
Deep learning also part 2 please
Can you kindly share your slides? Thanks
Thanks for the informative video
Very informative
Image base dataset pr dl and ml apply kry please please please please
Thank you so much sir...🎉🎉🎉
😢Sir your lecture can be more interesting by introducing
Little bit jokes just like your NLP lecture. It was learning with enjoying🎉
thankyou😍☺
Thanks
😇😇😇 thanks for sharing 😊
Please create video on Mojo programming language
Sir recurrent neural network ka video laiye
Video for making video on "how to make ai chatbot development" ❤
Deep learning part 2 ( Advanced Deep Learning )
Mam plz bta dai agr ghlti sy tiktok py pic upload ho jy or usko forn dlet kr dain to wo followers ky pass to nhi jy ge
Where can I get Datasets used in this video.
Excellent content! Need more ❤❤❤
I am very excited 🥰🥰
thankyou
Part 2 please
Yes Definitely Vote for Machine Learning Part 2...❤❤❤
Hello sir
Want to part 2🙏
Machine learning part 2 please 😢
Coming soon
I liked first 😂❤
Thank you so much for this topic ❤
mam machine learning ka part 2 kb ayega
Mam machine learning ka part 2 kb ayega ❤❤❤❤ please launch quickly. Our exams come near
Dataset bhi de diya kro yrr 😥😥😥
part 2 please 😊
Ya pir koi best youtube channel bata da jis sa ma AI learn kr sko in hindi ya urdu . I ma waiting your replay
Nutral nahi neural
Prerequisites for this video?
Best free resources always available here ❤ .
Machine learning part 2
bss DL ka yei part hy? 2nd part nye hy iska kya?
Share the dataset link
Love From Pakistan, good videos
sir pdf mil saktha hai plz send kar de
we need machine learning part 2
Artificial intelligence course need mam
Lots of love❤ from Pakistan 🇵🇰🇵🇰
Are ye excel sheet kaha pr milegi
ML p2
Sir artificial intelligence ka couse to upload kr da
we need part 2 of ml
Notespdf please sir
Sir plsss provide ml projects
Yes we want part 2 ML
Advanced deep learning part 2
Machine learning prt 2
How to get that android hacking couse back sir
Waiting for Deep Leaning part 2 😢
ML part 2
Deep learning 2nd part please please please please please upload upload upload upload upload upload