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RegenerativeToday
United States
เข้าร่วมเมื่อ 27 มี.ค. 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.
Principal Component Analysis in Python - Two Use Cases in Details
Principal Component Analysis is one of the most popular unsupervised machine learning techniques for dimensionality reduction. This tutorial includes a high-level overview of Principal Component Analysis, and two use cases of principal component analysis in details step by step in Python.
The first use case is to use principal component analysis to visualize the data and find the clusters or patterns.
The second use case is to use principal component analysis to reduce the dimension of a large dataset and only use the amount needed to have 95% of the variance of the dataset. So we can use a smaller dataset with less noise to train the machine-learning model much efficiently.
#machinelearning #machinelearningwithpython #python #artificialintelligence #unsupervisedlearning #PCA
The first use case is to use principal component analysis to visualize the data and find the clusters or patterns.
The second use case is to use principal component analysis to reduce the dimension of a large dataset and only use the amount needed to have 95% of the variance of the dataset. So we can use a smaller dataset with less noise to train the machine-learning model much efficiently.
#machinelearning #machinelearningwithpython #python #artificialintelligence #unsupervisedlearning #PCA
มุมมอง: 43
วีดีโอ
K Means Clustering in Python | How K Means Works | Find the Right K | Unsupervised Learning 2
มุมมอง 12421 วันที่ผ่านมา
This is a detailed video on KMeans clustering. It has a thorough description of the working process of the KMeans clustering. Then walking through the code on how to develop a KMeans clustering algorithm and show how to find the right K for the KMeans clustering algorithm. The official documentation for KMeans clustering of the sklearn library: scikit-learn.org/stable/modules/generated/sklearn....
What is Unsupervised Machine Learning | Unsupervised Learning 1
มุมมอง 35หลายเดือนก่อน
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?
มุมมอง 126หลายเดือนก่อน
With the advancement of AI, students are getting confused, about whether we need to learn data analysis, visualization, machine learning, or deep learning anymore. This video explains the overall data analytics projects and the general workflow to provide an understanding.
XGBoost Regressor in Python - sklearn
มุมมอง 113หลายเดือนก่อน
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
มุมมอง 94หลายเดือนก่อน
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
มุมมอง 67หลายเดือนก่อน
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...
Ada Boost Algorithm Clearly Explained
มุมมอง 49หลายเดือนก่อน
This video explains the Ada Boost machine learning algorithm. I took one simple dataset and showed all the calculations step by step very clearly. The prerequisite to understand this algorithm is to understand decision tree algorithm. Hopefully, after watching this video you will be able to visualize what goes on behind the scene of this machine learning algorithm even if you use a library or p...
Gradient Boosting Machine Classifier in Python
มุมมอง 1132 หลายเดือนก่อน
Gradient Boosting Machine is a popular ensemble machine learning method. It uses a series of weak models sequentially to improve the model's performance based on the errors of the previous model. The idea is to find out if there is any pattern in the residuals or errors and use that to improve the model's performance further. In my last video, I explained the intuition behind the Gradient Boost...
Gradient Boosting Machine - Easy Explanation | Regression in Python
มุมมอง 2012 หลายเดือนก่อน
Gradient Boosting Machine is an ensemble method in machine learning. It uses a series of weak models sequentially to improve the model accuracy based on the errors of the previous model. The idea is to find out if there is any pattern in the residuals or errors. In this tutorial, you will get the intuition on how the gradient boosting machine works with an example and then we will develop a reg...
K Nearest Neighbors Algorithm in Python | Classification | Regression | How to Choose the Right K
มุมมอง 2572 หลายเดือนก่อน
K-Nearest Neighbor algorithm is one of the simplest and still popular machine learning models out there. If a simple model can do the job, I would never go for a harder one. Simply because simple models are easier to explain to the stakeholders. This tutorial will cover everything you need to know to use a KNN classifier and a KNN Regressor for your project. This tutorial starts with a overview...
Learning Rate Scheduler in Keras and TensorFlow -
มุมมอง 1033 หลายเดือนก่อน
The Learning rate is arguably the most important hyperparameter in TensorFlow models. Keeping the learning rate the same throughout the model training may work but not always. If you notice any curve for losses in the training periods, it is normal for the model to learn really fast in the beginning and very slow at the end. So, models learn at different rates in the different stages of trainin...
Wide and Deep Learning in TensorFlow | Deep Learning Tutorial
มุมมอง 1193 หลายเดือนก่อน
If used correctly wide and deep learning techniques in neural networks can make it very efficient. It provides you with the flexibility of passing some features directly to the output and passing some features through a deep neural network. Or, you can pass the same features to the output directly and through a neural network at the same time. The complete code for this tutorial will be found h...
Neural Network With Functional API in TensorFlow | Deep Learning
มุมมอง 1414 หลายเดือนก่อน
Neural Network With Functional API in TensorFlow | Deep Learning
Saving And Loading TensorFlow Models - ModelCheckpoint Callback | Deep Learning With TensorFlow
มุมมอง 2174 หลายเดือนก่อน
Saving And Loading TensorFlow Models - ModelCheckpoint Callback | Deep Learning With TensorFlow
Analyzing Deep Learning Models with TensorBoard | TensorFlow, Keras, and Python
มุมมอง 2405 หลายเดือนก่อน
Analyzing Deep Learning Models with TensorBoard | TensorFlow, Keras, and Python
Callbacks, Early Stopping, Live Loss Plotting | Deep Learning | Keras, TensorFlow, and Python
มุมมอง 2305 หลายเดือนก่อน
Callbacks, Early Stopping, Live Loss Plotting | Deep Learning | Keras, TensorFlow, and Python
Regression Using TensorFlow, Keras, and Python - Complete Step by Step Tutorial
มุมมอง 2296 หลายเดือนก่อน
Regression Using TensorFlow, Keras, and Python - Complete Step by Step Tutorial
Build a Neural Network with TensorFlow, Keras, and Python
มุมมอง 7006 หลายเดือนก่อน
Build a Neural Network with TensorFlow, Keras, and Python
Cost Functions For Classification Models - Machine Learning
มุมมอง 2966 หลายเดือนก่อน
Cost Functions For Classification Models - Machine Learning
Cost Function Options for Regression Models- Machine Learning and Deep Learning
มุมมอง 1536 หลายเดือนก่อน
Cost Function Options for Regression Models- Machine Learning and Deep Learning
Neural Networks Explained Clearly - Step By Step
มุมมอง 3427 หลายเดือนก่อน
Neural Networks Explained Clearly - Step By Step
Feature Selection in Python - Wrapper Method
มุมมอง 2577 หลายเดือนก่อน
Feature Selection in Python - Wrapper Method
Feature Selection in Python - Feature Importance
มุมมอง 3207 หลายเดือนก่อน
Feature Selection in Python - Feature Importance
Feature Selection in Python - SelectKBest
มุมมอง 8008 หลายเดือนก่อน
Feature Selection in Python - SelectKBest
Feature Selection in Python - Correlation Matrix
มุมมอง 4788 หลายเดือนก่อน
Feature Selection in Python - Correlation Matrix
Natural Language Processing | Twitter Sentiment Analysis in Python
มุมมอง 3648 หลายเดือนก่อน
Natural Language Processing | Twitter Sentiment Analysis in Python
Natural Language Processing | Text Pre-Processing For Machine Learning in Python
มุมมอง 2118 หลายเดือนก่อน
Natural Language Processing | Text Pre-Processing For Machine Learning in Python
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: th-cam.com/video/km71sruT9jE/w-d-xo.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: th-cam.com/video/F13Wbfkpwlw/w-d-xo.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: th-cam.com/video/Hs_03ALPgjk/w-d-xo.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 TH-cam 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: th-cam.com/video/km71sruT9jE/w-d-xo.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 TH-cam. 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
Awesome as usual! You deserve way more recognition. As an HR professional, your videos help me apply ML into the HR field for classification problems and you have the best explanation for KNN. Thank you!
Thank you for the excellent post; what about other statistics like R-squared and correlation coefficient? Have you thought about the multivariate polynomial equation model? As you mentioned, training is overfitting but validation is very poor. Any suggestions are welcome.
If you are using this for a real world project, first try with different polynomial first and if you still do not get good results try other models. Usually for real world projects we try several different models with different parameters and finalize the best one.
@@regenerativetoday4244 Yes, I am using a real-world problem and trying to start with it before trying others.
@@regenerativetoday4244 Actually, I want to establish an empirical equation, as most of the other models are black boxes without equations.
Very well explained 🎉🎉 Thanks you so much 🎉🎉🎉
Thank you so much, u really explained everything so well
thank you so much
Very good video. About the model, dont you need to check if R-square need an adjust to trust his income?
There are a few different ways to check the model prediction. R-squared error is one of them. It is common for machine learning models to use mean squared error or mean absolute error as well.
Thanks for the amazing insights!
Please can you send me any link for case study using python polynomial regression (or multi polynomial) with data ? I want to practice.
Here it is: th-cam.com/video/nqNdBlA-j4w/w-d-xo.html
@RegnerativeToday Do you mind sharing your note book publicly so we learners can clone and play with it? Thank you in advance.
I added the notebook in the description box. Also here for you: github.com/rashida048/TensorFlow-Tutorial/blob/main/TensorFlow_NN.ipynb. Thank you!
How do we access the dataset used?
my last stop. Great job done.
goated thank you!
I really like you, can you guide me how to build a KNN model and choose its parameter K?
This channel is super under-rated
Its showing a error as "df isn't defined "
This contained so much information in such a short time frame. Very Well prepared. :)
Is Learning deep learning relevant today? Now that LLMs are in place. Any model I want to build is already been built.