- 115
- 381 337
RegenerativeToday
United States
Registrace 27. 03. 2020
This channel is dedicated to learners who wants to learn Data Science and Data Analytics. Most of the videos will be about Data Science tutorial. Starting from Python Data Analysis libraries like Numpy, Pandas, Matplotlib snd Scikit-Learn. The plan is to eventually move to Machine learning and deep earning tutorials. We will also develop algorithm and problem solving skills together. Our plan is to create a group of Data Scientists and Data analysts to learn from each other and help each other grow. We hope to be interactive in this this channel through constructive comments. Please subscribe and stay tuned if you want to keep learning with us.
What is Blockchain and How it is Different
In this video, "What is Blockchain and How It is Different," you’ll get a clear, easy-to-understand explanation of the blockchain technology that’s transforming industries worldwide. Whether you’re new to the concept or looking to deepen your understanding, this video breaks down the fundamentals of how blockchain works, its key features, and why it’s considered revolutionary. Learn how blockchain differs from traditional databases, focusing on its decentralized nature, security through cryptography, and the transparency it offers across various sectors like finance, healthcare, and supply chain management. You’ll also explore the differences between public and private blockchains, how cryptocurrencies like Bitcoin use blockchain, and its potential applications beyond digital currencies. Whether you're interested in tech, finance, or innovation, this video will give you a comprehensive overview of blockchain technology and how it stands out in the digital landscape. Perfect for beginners and tech enthusiasts alike!
zhlédnutí: 22
Video
Implementation of Recurrent Neural Network in TensorFlow | Natural Language Processing
zhlédnutí 36Před 19 hodinami
In this tutorial, learn how to implement a simple Recurrent Neural Network (RNN) in TensorFlow, with a focus on Natural Language Processing (NLP). This video guides you step-by-step through building and training an RNN model to process sequential text data, making it ideal for tasks like text classification, language modeling, and sentiment analysis. Designed for both beginners and intermediate...
The Evolution of Self Driving Cars in Brief
zhlédnutí 56Před 14 dny
Explore the fascinating journey of self-driving cars in this brief but comprehensive overview. This video takes you through the key milestones in the evolution of autonomous vehicles, from early concepts and prototypes to the cutting-edge technology used today. Learn about the major advancements in artificial intelligence, machine learning, and sensor technology that have made self-driving cars...
Build A Convolutional Neural Network in TensorFlow and Python | KerasTuner - Hyperparameter Tuning
zhlédnutí 90Před 21 dnem
Ready to dive into deep learning? This tutorial will guide you step-by-step in developing a Convolutional Neural Network (CNN) using TensorFlow and Python. Ideal for beginners and intermediate learners, this video breaks down complex concepts into easy-to-understand segments, helping you build your first CNN from scratch. You’ll learn how to set up your environment, preprocess data, construct t...
How to Stay Relevant in the AI Job Market
zhlédnutí 51Před 28 dny
Staying relevant in the AI and tech job market requires continuous learning and adaptability. Start by keeping up with the latest industry trends and technologies through online courses, webinars, and tech blogs. Engaging in professional networks and communities can also provide insights into emerging tools and practices. Building a diverse skill set is crucial; focus on acquiring both technica...
Human Brain on a Robot Body?
zhlédnutí 99Před měsícem
"Human Brain on a Robot Body?" explores the cutting-edge intersection of neuroscience and robotics. This intriguing concept delves into the future of integrating human cognitive functions with advanced robotic systems. Imagine a future where a human brain can control a robotic body, offering limitless possibilities for mobility, precision, and new forms of interaction. This video examines the l...
Principal Component Analysis in Python - Two Use Cases in Details
zhlédnutí 113Před měsícem
"Principal Component Analysis in Python - Two Use Cases in Detail" offers a comprehensive guide to mastering PCA, a powerful dimensionality reduction technique. This video provides an in-depth exploration of PCA with practical Python implementations, showcasing two detailed use cases. First, we demonstrate PCA for enhancing data visualization by reducing complex datasets into 2D or 3D formats, ...
K Means Clustering in Python | How K Means Works | Find the Right K | Unsupervised Learning 2
zhlédnutí 154Před 2 měsíci
"K Means Clustering in Python | How K Means Works | Find the Right K | Unsupervised Learning 2" is your ultimate guide to mastering K Means Clustering, a fundamental technique in unsupervised learning. In this video, we break down the K Means algorithm step-by-step, explaining how it partitions data into clusters based on similarity. Learn how to implement K Means in Python using libraries like...
What is Unsupervised Machine Learning | Unsupervised Learning 1
zhlédnutí 81Před 2 měsíci
Unsupervised Learning is another big part of Machine Learning. In Unsupervised Learning, prediction is not the goal. The idea is to understand the data better and find a structure in a big dataset. Unsupervised Learning can be used to prepare data for Supervised Learning for a lot of time. #artificialintelligence #machinelearning #datascience #unsupervisedlearning
Do We Need to Learn Machine Learning / Deep Learning Anymore | Can AI Do the Model Now?
zhlédnutí 148Před 2 měsíci
In an era where artificial intelligence rapidly evolves, many question if learning machine learning (ML) and deep learning (DL) are still necessary. With AI technologies advancing, automated tools now assist in model development, making it easier for non-experts to implement complex algorithms. However, understanding the fundamentals of ML and DL remains crucial for innovation and problem-solvi...
XGBoost Regressor in Python - sklearn
zhlédnutí 148Před 2 měsíci
This is a complete tutorial on XGBoost regressor in Python - sklearn. Each step is explained in detail. The complete working code on XGBoost Classifier in sklearn is here: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/XGBoost_Regressor.ipynb The dataset used in this tutorial: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/Housing.csv The Offici...
XGBoost Classifier in Python - Multiple Disease Prediction
zhlédnutí 132Před 3 měsíci
XGBoost or eXtreme Gradient Boosting is a very popular implementation of the Gradient Boosting algorithm. This tutorial shows some important aspects of it, parameters, and the implementation of a classification model in Python. The dataset used in this tutorial: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/multiple_disease_dataset.csv The complete code of this tutoria...
Ada Boost Classifier in Python
zhlédnutí 88Před 3 měsíci
This is a complete tutorial on Ada Boost Classifier in Python's scikit-learn package. The dataset used in this tutorial: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/multiple_disease_dataset.csv The complete code of this tutorial: github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/AdaBoostClassifier.ipynb The video explains in detail how the Ada B...
Gradient Boosting Machine Classifier in Python
zhlédnutí 122Před 3 měsíci
Gradient Boosting Machine Classifier in Python
Gradient Boosting Machine - Easy Explanation | Regression in Python
zhlédnutí 248Před 4 měsíci
Gradient Boosting Machine - Easy Explanation | Regression in Python
K Nearest Neighbors Algorithm in Python | Classification | Regression | How to Choose the Right K
zhlédnutí 315Před 4 měsíci
K Nearest Neighbors Algorithm in Python | Classification | Regression | How to Choose the Right K
Learning Rate Scheduler in Keras and TensorFlow -
zhlédnutí 133Před 4 měsíci
Learning Rate Scheduler in Keras and TensorFlow -
Wide and Deep Learning in TensorFlow | Deep Learning Tutorial
zhlédnutí 126Před 5 měsíci
Wide and Deep Learning in TensorFlow | Deep Learning Tutorial
Neural Network With Functional API in TensorFlow | Deep Learning
zhlédnutí 158Před 5 měsíci
Neural Network With Functional API in TensorFlow | Deep Learning
Saving And Loading TensorFlow Models - ModelCheckpoint Callback | Deep Learning With TensorFlow
zhlédnutí 274Před 5 měsíci
Saving And Loading TensorFlow Models - ModelCheckpoint Callback | Deep Learning With TensorFlow
Analyzing Deep Learning Models with TensorBoard | TensorFlow, Keras, and Python
zhlédnutí 268Před 6 měsíci
Analyzing Deep Learning Models with TensorBoard | TensorFlow, Keras, and Python
Callbacks, Early Stopping, Live Loss Plotting | Deep Learning | Keras, TensorFlow, and Python
zhlédnutí 258Před 6 měsíci
Callbacks, Early Stopping, Live Loss Plotting | Deep Learning | Keras, TensorFlow, and Python
Regression Using TensorFlow, Keras, and Python - Complete Step by Step Tutorial
zhlédnutí 267Před 7 měsíci
Regression Using TensorFlow, Keras, and Python - Complete Step by Step Tutorial
Build a Neural Network with TensorFlow, Keras, and Python
zhlédnutí 874Před 7 měsíci
Build a Neural Network with TensorFlow, Keras, and Python
Cost Functions For Classification Models - Machine Learning
zhlédnutí 367Před 8 měsíci
Cost Functions For Classification Models - Machine Learning
Cost Function Options for Regression Models- Machine Learning and Deep Learning
zhlédnutí 165Před 8 měsíci
Cost Function Options for Regression Models- Machine Learning and Deep Learning
Neural Networks Explained Clearly - Step By Step
zhlédnutí 394Před 8 měsíci
Neural Networks Explained Clearly - Step By Step
very good
Thank you so much for your simplistic explanations!
Nice❤
Nice class thanks
Good tutorial!
Madam I practiced self driving car code by Yolo and CNN can you make a video regarding coding
its really helpfull thanks alot
dfs.loc[idx['school1':'school3', 2019:2020], idx['7th grade':'8th grade', 'Math':'English']] I am getting UnsortedIndexError: 'Key length (2) was greater than MultiIndex lexsort depth (1)' and UnsortedIndexError: 'MultiIndex slicing requires the index to be lexsorted: slicing on levels [0, 1], lexsort depth 1' error. Can you please help. I am also getting the same error for dfs.loc[('school1', 2019):('school3', 2020),('7th grade', 'Math'):('8th grade','Math')]
Nice class👌
Madam can you please suggest me a laptop for aiml
🙏👍🇵🇰
Slowing down, zooming out and picking up new skills if they resonate with us. Thank you so much for the the great content!
Thanks.
why did we convert it the training data to 2d?
This is a general rule. Scikit learn library takes the features as 2D. Either DataFrames or 2d arrays.
Madam suggest any website link for machine learning job's in India
Excellent Explanation and with great concept...Thank you very much👍
thank you very much this helped me a lot hopefully, I will get a good grade !! :)))
Great video. Please can you share the insurance data? It's not visible in the description. Thank you
Why did we use poly.fit, when we already used poly.fit_transform 08:37
could u plz provide the Dataset being used in the video
why did u choose degree 6?
That's just an estimate. degree is a hyperparameter here that you need to try different values to find the right one for you. Look at this video where you will find a method to tune the hyperparameter faster: czcams.com/video/km71sruT9jE/video.html
Thanks for the video. A question: is poly.fit(X_poly_train, y_train) necessary?
Audio is not clear and your voice is also not audible
hi, I'm not able to find your video on improving the R2 score. Can you show me the video? Thanks
You can watch this one that shows how to fine tune hyperparameters that should improve R2 score: czcams.com/video/F13Wbfkpwlw/video.html
Thank you! this is excellent
It is best video for new learners
Madam can you prefer me any job link regarding AI ML jobs to me
nice video, thanks for your effort ❤
Madam need kmeans clustering and hierarchical clustering
Coming next..Thank you!!
I enjoy your tutorials. Thank you
I think its the best video of Correlation Matrix and Heatmap in Python, i have seen many videos but you teaching skill is best . Keep upload the videos and spread the knowledge , we will support you.
Your videos are truly remarquable. I’ve been also amazed by your simple explanations and tutorials. Do you offer mentorship for people wanting to learn more about data science or online sessions as a service? If so it would be great to get more informations. Keep up the good work!
sister thank you. one request kindly make a list of your videos in chronological order so that we know which video to follow first.
Please check the playlist. Each playlists are almost organized. Here is the playlist for the Supervised Machine Learning: czcams.com/video/Hs_03ALPgjk/video.html
@@regenerativetoday4244 thanks
at last something hands on with real problems. I'm tired of maths abstract bullshit formulas....
thank you! how to know p_value and if the coefficient is significant or not?
Thank you...
wonderful way to simplify a diffcult topic to beginners. keep it up!
Take better mic or make any post processing bruh. Your audio quality ve not increased for 2 years
Mam you explained so good!! Mam how can I see the equation made by my Decision Tree?
Amazing Mam!! very Wonderfully explained!!
I gone through all the videos of machine learning in your CZcams channel madam but I need some guidance to get on job experience how it works
Do you have any specific question? If you want a job, you simply need to apply for jobs. If you can get some referral that helps.
@@regenerativetoday4244 I completed my btech graduation madam now I am practicing ai&ml in NIMSE institute Hyderabad
@@regenerativetoday4244 I need guidance for machine learning and deep learning notes
Madam I need guidance lines for AI&ML please help me
Thank you mam for such a wonderful learning!! I want to know further how can I improve my model accuracy with train score 0.75 and test score -1.12 ??
First is trying to tune hyperparameters, and also it is normal practice to try different models to find out which model works best for the dataset. Feel free to have a look at this video where you will find a technique for hyperparameter tuning: czcams.com/video/km71sruT9jE/video.html
@@regenerativetoday4244 Thank you so much you have explained it Amazingly and this video made me very happy! Thank you for this video all the rest!!
Request for more Machine Learning Videos in details.
Thank you Mam you taught me linear regression in very simple and expert way!! I saw many videos and you will be amazed to know that you are the BEST!!
I discovered your Pandas MultiIndex and XS while browsing through the CZcams. Very well explained and it really helped me to build these concepts.
Just an Brilliant Explanation Mam
Data isn't my background, but these videos help me understand how to structurally get there. Is there a way to export the predicted charges into a data population for further review. Also, is there a way to adjust the scatter plot dots by a filter on one of the independent variables (i.e. any record where age is 17, make the the plot red color). Thank you!
very detailed ...nice
how do input new input values and predict a value for them