Bro then you should focus on basics projects as some of them has mentioned in the video but if you have a fyp group of 3 students then you should not try the basic projects but intermediate projects.
aoa bro main ne AI based career counseling platform ka final year project banana hai but i dont have experience in it what i do now kindly guide me as it will be helpful in my future
Here's a brief structure and steps to build a fake review detector using AI: 1. Data Collection: - Gather a dataset of reviews labeled as real or fake. 2. Preprocessing: - Clean and tokenize the text data. - Perform feature engineering, like TF-IDF or word embeddings. 3. Model Selection: - Choose a machine learning or deep learning model (e.g., LSTM, BERT). 4. Model Training: - Train the model on the labeled data. 5. Evaluation: - Assess the model's performance with metrics like accuracy and F1 score. 6. Fine-Tuning: - Refine the model by adjusting hyperparameters. 7. Deployment: - Integrate the model into an application or service for real-time detection. 8. Continuous Improvement: - Continuously update the model with new data for better accuracy. 9. Monitoring: - Implement monitoring to detect model drift and maintain accuracy over time. 10. Scaling: - If necessary, scale the system to handle a large volume of reviews. Remember to maintain ethical considerations while building and deploying such systems.
3:50 thank me later
thanks bro you have saved my time
thank you nigga
Thank you 😊
Thank you 😊
Thank you for the precious 1 minute 55 seconds
one complete project video (including deployment) e.g. Color image using CIFAR 10 data set. It will help a lot. Thanks for the project recomendation.
Thank you so much sir ❤
such an amazing ,unique and intresting projects
Hm
Amazing ❤️
Bro mny AI ka project bnana h lkn mn beginner hn mjy bilkul b idea ni k kasy project bnaty hain,even k python b ni ati, kindly guide kr skty ho?
Bro then you should focus on basics projects as some of them has mentioned in the video but if you have a fyp group of 3 students then you should not try the basic projects but intermediate projects.
Sir ap koi project banao aur uska code source bhi dona
I need these topics for my mini-project, can I use them for it ?
bhaiya mujhe end sem ke liye ek major project banana h jo kuch unique ho please suggest kardo
Hi @LofiBot11. Mai aapko help kar sakta hu end sem ke project ke liye.. Interested ho to contact details message karo.
Sir chatbot project python step by step video upload kar dona sir
bro can you please suggest best course on youtube/any other platform to learn ai and ml
andrew ng courses for machine learning
@@uncover_ai is that a complete course ? it showing around 20 videos
aoa bro main ne AI based career counseling platform ka final year project banana hai but i dont have experience in it what i do now kindly guide me as it will be helpful in my future
Sir Apka Education Background kya hai ap kis College se ho
Can you say wt are prerequisite courses to be learn to create fake review detection project
And steps to follow
hlo sir ,
i'm Naveekumar y m , i purcheased the 5days live course and also paied the 299 rupee money so then how can i access the course
You will receive email or call from team before class start dont worry
Sir , how we Handwriting Detect ?
bro i want to create website like Elevenlab is it possible for me to develop website like elevenlab which convert text to speech
Kha se sikh skta hu main in sb languages ko jo AI me help kr skta h
700+ Ready-made Programming projects code but this is not free😕
bot telegram bot banan batao
Source code diya karo bhai
I am in class 7
Good
That's why you're using Free picture as your dp
Fake Review detector kaise banaye?
Here's a brief structure and steps to build a fake review detector using AI:
1. Data Collection:
- Gather a dataset of reviews labeled as real or fake.
2. Preprocessing:
- Clean and tokenize the text data.
- Perform feature engineering, like TF-IDF or word embeddings.
3. Model Selection:
- Choose a machine learning or deep learning model (e.g., LSTM, BERT).
4. Model Training:
- Train the model on the labeled data.
5. Evaluation:
- Assess the model's performance with metrics like accuracy and F1 score.
6. Fine-Tuning:
- Refine the model by adjusting hyperparameters.
7. Deployment:
- Integrate the model into an application or service for real-time detection.
8. Continuous Improvement:
- Continuously update the model with new data for better accuracy.
9. Monitoring:
- Implement monitoring to detect model drift and maintain accuracy over time.
10. Scaling:
- If necessary, scale the system to handle a large volume of reviews.
Remember to maintain ethical considerations while building and deploying such systems.
@@codingwithsagarcw Hey! Im planning to implement this using FPGA. Can you help me out with it. Thanks.
Yaar Jo title lagaya hai wo nahi bolte ho .. time berbad kerte ho .. bakwas ..
Explain??
sorry to say but your background music is irritating! bye
3:50 thank me later
Mention project names also