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Rachit Toshniwal
United States
Приєднався 13 січ 2012
Hello,
I'm Rachit Toshniwal, and I'm trying to make sure there aren't many entry barriers to data science... (errr... well, there are a few barriers beyond my control, like getting distracted by mobile notifications while studying, etc xD)
Let me know if there is any way my content can be improved, or if you find my content unclear. I'm all ears for suggestions :)
Thanks, and I hope you like my videos!
I'm Rachit Toshniwal, and I'm trying to make sure there aren't many entry barriers to data science... (errr... well, there are a few barriers beyond my control, like getting distracted by mobile notifications while studying, etc xD)
Let me know if there is any way my content can be improved, or if you find my content unclear. I'm all ears for suggestions :)
Thanks, and I hope you like my videos!
Removing constant & Quasi constant features using Variance Threshold | Machine Learning
#variancethreshold #constant #quasiconstant
In this video, we will look at how we can effortlessly remove constant and quasi constant features from our datasets and make them leaner and more robust, using scikit-learn's VarianceThreshold implementation.
I've uploaded all the relevant code and datasets used here (and all other tutorials for that matter) on my github page which is accessible here:
Link:
github.com/rachittoshniwal/machineLearning
If you like my content, please do not forget to upvote this video and subscribe to my channel.
If you have any qualms regarding any of the content here, please feel free to comment below and I'll be happy to assist you in whatever capacity possible.
Thank you!
In this video, we will look at how we can effortlessly remove constant and quasi constant features from our datasets and make them leaner and more robust, using scikit-learn's VarianceThreshold implementation.
I've uploaded all the relevant code and datasets used here (and all other tutorials for that matter) on my github page which is accessible here:
Link:
github.com/rachittoshniwal/machineLearning
If you like my content, please do not forget to upvote this video and subscribe to my channel.
If you have any qualms regarding any of the content here, please feel free to comment below and I'll be happy to assist you in whatever capacity possible.
Thank you!
Переглядів: 3 221
Відео
Principal Component Analysis (PCA) Intuition | Machine Learning
Переглядів 9683 роки тому
#pca #machinelearning #intuition In this video, we'll look at WHAT and the HOW of PCA. Thanks!
Machine Learning Project | Credit Risk Analysis | Learning Curves | Overfitting | Python
Переглядів 22 тис.3 роки тому
#machinelearning #python #project In this video we will look at a Machine Learning project that will try to predict whether someone will get their loan sanctioned or not. We will use a Randomized Search too find optimal set of parameters. We will then use precision recall curves and learning curves to assess the model performance. We will rectify the case of overfitting in the model and make am...
Machine Learning Project | Predicting Student Marks | Python
Переглядів 8 тис.3 роки тому
#ml #project #python In this video, we will make a quick and dirty ML model to predict the marks of a student. We will do some basic EDA, then use Column Transformers and Pipelines to make the model, use the GridSearchCV to find the best performing model and then save it using joblib. The link to the data and the notebook can be found here: github.com/rachittoshniwal/ML-projects/ Hope it helps!
How to tune hyper parameters using Grid Search CV | With and without a Pipeline | Machine Learning
Переглядів 5 тис.4 роки тому
#grisdearch #machine #learning #python In this tutorial, we'll look at Grid Search CV, a technique by which we can find the optimal set of hyper-parameters and fine tune our ML model to make a better model. Table of contents: 0:00 Intro 1:08 Randomized Search CV 1:52 Python code for Grid Search CV 3:20 Without a pipeline 8:21 With a pipeline I've uploaded all the relevant code and datasets used...
Churn Modeling Tableau Project for beginners
Переглядів 22 тис.4 роки тому
#tableau #project #beginners In this video, we'll build a simple Tableau dashboard for analyzing customer churn at a bank. We'll use filters, parameters, histograms, dashboard actions, and some formatting to prettify our viz. Table of contents : 0:01 Final dashboard 2:51 Making the sheets 16:08 Making the dashboard 22:50 Dashboard actions You can access the workbooks from my tableau public prof...
How to create and use groups to clean data and create higher level dimensions | Tableau Series
Переглядів 1154 роки тому
#tableau #groups In this video, we'll look at how to create and use groups in Tableau in two different scenarios: 0:01 Using groups for handling messy data 4:23 Using groups for creating higher level "positions" dimension You can access the workbooks from my tableau public profile: public.tableau.com/profile/rachit.toshniwal#!/ Link for all the relevant materials used in these videos: github.co...
How to split different records having same values in a column in Tableau | Tableau Series
Переглядів 5734 роки тому
#tableau In this video, we'll look at how to systematically organize fields into folders in Tableau. You can access the workbook from my tableau public profile: public.tableau.com/profile/rachit.toshniwal#!/ Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video, please consider subscribing to my channel and upvote this video! Thank y...
How to systematically organize fields into folders | Tableau Series
Переглядів 984 роки тому
#tableau #folders #organize In this video, we'll look at how to systematically organize fields into folders in Tableau. Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video, please consider subscribing to my channel and upvote this video! Thank you for watching!
How to create hierarchies in Tableau | Tableau Series
Переглядів 1574 роки тому
#tableau #hierarchies In this video, we'll look at how to create hierarchies in Tableau. Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video, please consider subscribing to my channel and upvote this video! Thank you for watching!
Using the replace function in tableau to clean messy columns | Tableau Series
Переглядів 4,5 тис.4 роки тому
#tableau #replace #function In this video, we'll look at how to use the in-built "replace" function in tableau to clean messy data. 0:01 Replace function in a calculated field 3:33 Exercises for solidifying concepts 4:17 Solutions for the exercises 7:08 Hiding the unwanted columns Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video...
Using the split function in a calculated field to clean messy data | Tableau Series
Переглядів 4744 роки тому
#tableau #split #calculated #field In this video, we'll look at how to use the in-built split function in Tableau to clean messy data. 0:17 Problems with using auto and custom split for non-uniform columns 1:55 Using split in a calculated field Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video, please consider subscribing to my c...
Using auto and custom split in Tableau to split columns | Tableau Series
Переглядів 3964 роки тому
#tableau #split #custom #auto In this video, we'll look at how to use the auto and custom split methods in Tableau to split string columns into n-number of different columns. 0:18 What is splitting and how does it happen? 1:41 Custom split 4:20 Auto split 6:49 Where auto split fails Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this vid...
Editing the metadata in Tableau | Tableau Series
Переглядів 4704 роки тому
#tableau #editing #metadata In this video, we'll look at how to edit the metadata in tableau, to make the data ready for analysis and drawing inferences from. Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video, please consider subscribing to my channel and upvote this video! Thank you for watching!
Data types in Tableau | Numeric, String, Geographic, Boolean, Date, Date & Time | Tableau Series
Переглядів 3504 роки тому
#tableau #data #types In this video, we'll look at the different data types in Tableau. Link for all the relevant materials used in these videos: github.com/rachittoshniwal/tableau If you like this video, please consider subscribing to my channel and upvote this video! Thank you for watching!
When to add a new connection vs a Data source in Tableau | Tableau Series
Переглядів 1,9 тис.4 роки тому
When to add a new connection vs a Data source in Tableau | Tableau Series
Unions in Tableau | How to use a wildcard for unions in Tableau | Tableau Series
Переглядів 8534 роки тому
Unions in Tableau | How to use a wildcard for unions in Tableau | Tableau Series
Blending multiple distinct data sources in Tableau | Tableau Series
Переглядів 2844 роки тому
Blending multiple distinct data sources in Tableau | Tableau Series
Joins in Tableau | Inner, Outer, Left and Right Joins | Physical and Logical Layer | Tableau Series
Переглядів 1,5 тис.4 роки тому
Joins in Tableau | Inner, Outer, Left and Right Joins | Physical and Logical Layer | Tableau Series
Relationships - The new Tableau data model | Understanding the Performance Options | Tableau Series
Переглядів 6104 роки тому
Relationships - The new Tableau data model | Understanding the Performance Options | Tableau Series
Connecting to a data source in Tableau | Different types of connections | Tableau Series
Переглядів 3404 роки тому
Connecting to a data source in Tableau | Different types of connections | Tableau Series
Downloading Tableau | Tableau Desktop or Tableau Public? Advantages and limitations | Tableau Series
Переглядів 4384 роки тому
Downloading Tableau | Tableau Desktop or Tableau Public? Advantages and limitations | Tableau Series
(Code) Iterative Imputer | MICE Imputer in Python | Machine Learning
Переглядів 14 тис.4 роки тому
(Code) Iterative Imputer | MICE Imputer in Python | Machine Learning
(Code) What is Winsorization | Using percentiles for capping outliers in Python | Machine Learning
Переглядів 6 тис.4 роки тому
(Code) What is Winsorization | Using percentiles for capping outliers in Python | Machine Learning
(Code) Trimming outliers using the IQR method | Machine Learning
Переглядів 2,3 тис.4 роки тому
(Code) Trimming outliers using the IQR method | Machine Learning
(Code) Capping outliers using the IQR method | Machine Learning
Переглядів 6 тис.4 роки тому
(Code) Capping outliers using the IQR method | Machine Learning
Using IQR for handling outliers | Calculating Percentiles | Inner & Outer Fences | Machine Learning
Переглядів 6254 роки тому
Using IQR for handling outliers | Calculating Percentiles | Inner & Outer Fences | Machine Learning
(Code) Trimming outliers using the Z-score method | Machine Learning
Переглядів 1,1 тис.4 роки тому
(Code) Trimming outliers using the Z-score method | Machine Learning
(Code) Capping outliers using the Z-score method | Machine Learning
Переглядів 1,9 тис.4 роки тому
(Code) Capping outliers using the Z-score method | Machine Learning
When to and when NOT to use Z-scores for handling outliers | Machine Learning
Переглядів 7964 роки тому
When to and when NOT to use Z-scores for handling outliers | Machine Learning