Kakamana’s Blogs
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Kakamana’s Blogs

Configuring and Connecting to a PostgreSQL Database with Docker

docker
PostgreSQL
This article is about configuration, creation & connection of PostgreSQL through docker. Although this article is very basic in nature, but can be useful for future reference when configuring, setting up and connecting to PostgreSQL database through docker container
Mar 28, 2024
kakamana
4 min

Unraveling the Impact of Randomization Techniques: A Case Study on Uber’s Tipping Experiment

python
university of michigan
randomization
statistical analysis
This post is continuation of my understanding about experimental design & analysis, here I am trying to discuss about randomization technique with help of uber tipping experiment use case for their drivers conducted couple of years back.
Mar 25, 2024
kakamana
4 min

Facial Expression Recognition with Keras

python
deep learning
machine learning
cnn
neural network
keras
tensorflow
face recognition
This Facial Expression Recognition with Keras is part of Coursera Project: Facial Expression Recognition with Keras. We will build and train a convolutional neural network…
Jun 2, 2023
kakamana
6 min

Decision Trees

python
deep learning.ai
machine learning
supervised learning
linear regression
neural network
In this notebook you will visualize how a decision tree is split using information gain.
May 13, 2023
kakamana
7 min

Tree Ensembles

python
deep learning.ai
machine learning
decision tree
random forest
xgboost
In this lab, you will Work with a dataset related to cardiovascular disease, Build three different models to estimate how likely a person is to develop cardiovascular…
May 13, 2023
kakamana
11 min

Diagnosing Bias and Variance

python
deep learning.ai
machine learning
supervised learning
bias
variance
underfit
overfit
neural network
This lab you will use measures of training error and cross validation error to diagnose either high variance and/or high bias, and take steps to address these.
May 12, 2023
kakamana
9 min

Back Propagation

python
deep learning.ai
machine learning
supervised learning
back propagation
neural network
This describes compute graphs and their use in back propagation. Working through this lab will give you insight into a key algorithm used by most machine learning…
May 9, 2023
kakamana
9 min

Derivatives

python
deep learning.ai
machine learning
supervised learning
back propagation
neural network
This lab gives you an intuitive understanding of derivatives prior to tackling back propagation. It gives understanding of derivatives. It will show you a simple way of…
May 9, 2023
kakamana
5 min

Model Evaluation and Selection

python
deep learning.ai
machine learning
supervised learning
linear regression
neural network
This you will practice how to quantify a learning algorithm’s performance and compare different models.
May 9, 2023
kakamana
12 min

Multi-class Classification

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
neural network
This notebook wille explore neural network with multi class classification
Apr 30, 2023
kakamana
7 min

Softmax Function

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
neural network
This lab is about softmax function, its usage in both softmax regression and in neural networks when solving multiclass classification
Apr 30, 2023
kakamana
7 min

ReLU activation

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
neural network
This lab is about basic understanding of relu activation function.
Apr 29, 2023
kakamana
5 min

Coffee roasting in tensorflow

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
neural network
This lab is about basic understanding of neuron & layers. Use of them through tensorflow and keras.
Apr 28, 2023
kakamana
7 min

Coffee roasting numpy

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
neural network
This lab is about basic understanding of neuron & layers. Use of them through tensorflow and keras.
Apr 28, 2023
kakamana
5 min

Neurons and Layers

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
neural network
This lab is about basic understanding of neuron & layers. Use of them through tensorflow and keras.
Apr 28, 2023
kakamana
4 min

Gradient Descent for Linear Regression

python
deep learning.ai
machine learning
supervised learning
Linear regression
gradient descent
you’ll take a look how the gradient for linear cost is calculated in code. This will be useful to look at because you will implement this in the practice lab at the end of…
Apr 27, 2023
kakamana
8 min

Classification

python
deep learning.ai
machine learning
supervised learning
logistic regression
classification
you’ll get to take a look at what happens when you try to use linear regression for classification on categorical data. You can see an interactive plot that attempts to…
Apr 25, 2023
kakamana
4 min

Cost function for logistic regression

python
deep learning.ai
machine learning
supervised learning
logistic regression
This optional lab will show you how the logistic cost function is implemented in code. You will get to implement this later in the practice lab at the end of the week.
Apr 25, 2023
kakamana
4 min

Decision boundary - classification with logistic regression

python
deep learning.ai
machine learning
supervised learning
logistic regression
classification
you’ll get to see the code implementation of the decision boundary. In this example, there will be two features, so you can see the decision boundary as a line
Apr 25, 2023
kakamana
5 min

Gradient Descent for Logistic Regression

python
deep learning.ai
machine learning
supervised learning
logistic regression
gradient descent
you’ll take a look how the gradient for logistic cost is calculated in code. This will be useful to look at because you will implement this in the practice lab at the end of…
Apr 25, 2023
kakamana
5 min

Logistic loss

python
deep learning.ai
machine learning
supervised learning
logistic regression
you’ll get to take a look at how the squared error cost doesn’t work very well for classification, because you’ll see a surface plot of a very wiggly cost surface with many…
Apr 25, 2023
kakamana
6 min

Logistic Regression using Scikit-Learn

python
deep learning.ai
machine learning
supervised learning
logistic regression
will show you how to use the popular sci-kit learn library to train a logistic regression model for classification.
Apr 25, 2023
kakamana
2 min

Sigmoid function and logistic regression

python
deep learning.ai
machine learning
supervised learning
logistic regression
sigmoid
you’ll get to see how the sigmoid function is implemented in code. You can see a plot that uses the sigmoid to improve the classification task that you saw in the previous…
Apr 25, 2023
kakamana
4 min

The problem of overfitting

python
deep learning.ai
machine learning
supervised learning
logistic regression
you’ll take a look at some examples of overfitting that you can adjust by clicking on the options in the plot. In the lab you’ll be able to add your own data points by…
Apr 25, 2023
kakamana
3 min

The problem of overfitting - Regularization

python
deep learning.ai
machine learning
supervised learning
logistic regression
linear regression
overfitting
rgularization
you’ll take a look at some examples of overfitting that you can adjust by clicking on the options in the plot. In the lab you’ll be able to add your own data points by…
Apr 25, 2023
kakamana
5 min

Feature engineering and polynomial regression

python
deep learning.ai
machine learning
supervised learning
polynomial regression
you’ll see some code that implements polynomial regression including features like x, x squared, and x cubed.
Apr 24, 2023
kakamana
6 min

Feature scaling and learning rate

python
deep learning.ai
machine learning
supervised learning
feature scaling
gradient descent
Additionally, this exercise allows you to examine how feature scaling is accomplished in code and how different choices of learning rate alpha can result in a better or…
Apr 24, 2023
kakamana
14 min

Linear regression with scikit-learn

python
deep learning.ai
machine learning
supervised learning
linear regression
A popular open source toolkit that implements linear regression is demonstrated in this optional lab. Open source machine learning library Scikit-Learn is used by many…
Apr 24, 2023
kakamana
3 min

Linear regression for multiple variables

python
deep learning.ai
machine learning
supervised learning
Linear regression
multiple variables
The objective of this optional lab is to demonstrate how to define a multiple regression model, in code, and how to calculate the prediction, f of x. Additionally, you will…
Apr 23, 2023
kakamana
11 min

Regression model representation

python
deep learning.ai
machine learning
supervised learning
regression
This Regression model representation is part of DeepLearning.AI course: Machine Learning Specialization / Course 1: Supervised Machine Learning: Regression and Classification…
Apr 16, 2023
kakamana
7 min

Vectorization with python and numpy

python
deep learning.ai
machine learning
supervised learning
vectorization
This optional lab will demonstrate how to use NumPy to implement vectors and matrices in code, and to perform dot products and matrix multiplications. Vectorization is used…
Apr 16, 2023
kakamana
10 min

Dive into the Competition

python
datacamp
machine learning
deep learning
As part of PySpark, cutting-edge machine learning routines are included, as well as utilities that can be used to create full machine learning pipelines. In this chapter…
Apr 14, 2023
kakamana
5 min

Feature Engineering - Kaggle competition

python
datacamp
machine learning
deep learning
As part of PySpark, cutting-edge machine learning routines are included, as well as utilities that can be used to create full machine learning pipelines. In this chapter…
Apr 14, 2023
kakamana
6 min

Kaggle competitions process

python
datacamp
machine learning
deep learning
As part of PySpark, cutting-edge machine learning routines are included, as well as utilities that can be used to create full machine learning pipelines. In this chapter…
Apr 14, 2023
kakamana
5 min

Modeling - Winning kaggle competition in python

python
datacamp
machine learning
deep learning
As part of PySpark, cutting-edge machine learning routines are included, as well as utilities that can be used to create full machine learning pipelines. In this chapter…
Apr 14, 2023
kakamana
6 min

Ensembles & Pipelines

python
datacamp
machine learning
pyspark
ensemble
pipeline
Finally, you will learn how to improve the efficiency of your models. By using pipelines, you will be able to make your code more clear and easier to maintain. To test your…
Apr 11, 2023
kakamana
6 min

Regression - machine learning with PySpark

python
datacamp
machine learning
pyspark
regression
Next, you will learn how to create linear regression models. In addition, you will learn how to augment your data with new predictors as well as how to select only the most…
Apr 10, 2023
kakamana
6 min

Classification in PySpark

python
datacamp
machine learning
PySpark
The next step is to build two types of classification models: Decision Trees and Logistic Regression. Additionally, you will learn about a few approaches to data preparation.
Apr 9, 2023
kakamana
6 min

Grid Search

python
datacamp
machine learning
deep learning
hyperparameter
gridsearch
The purpose of this chapter is to introduce you to a popular automated hyperparameter tuning method referred to as Grid Search. In this lesson, you will gain an…
Apr 9, 2023
kakamana
5 min

Hyperparameters and Parameters

python
datacamp
machine learning
deep learning
hyperparameter
The purpose of this introductory chapter is to explain the differences between hyperparameters and parameters. You will practice extracting and analyzing parameters, setting…
Apr 9, 2023
kakamana
5 min

Informed Search

python
datacamp
machine learning
deep learning
hyperparameter
In this final chapter, you will learn about more advanced hyperparameter tuning methodologies known as ‘’informed search’’. A coarse-to-fine methodology is included as well…
Apr 9, 2023
kakamana
6 min

Introduction of machine learning with pyspark

python
datacamp
machine learning
pyspark
Spark is a framework for working with large amounts of data. The purpose of this chapter is to provide some background information on Spark and Machine Learning. Afterward…
Apr 9, 2023
kakamana
4 min

Random Search

python
datacamp
machine learning
deep learning
hyperparameter
random search
In this chapter, you will be introduced to another popular automated hyperparameter tuning method known as Random Search. You will learn what it is, how it works, and how it…
Apr 9, 2023
kakamana
5 min

Advanced Operations, Detecting Faces and Features

python
datacamp
machine learning
deep learning
neural network
As a result of completing this chapter, you will have a deeper understanding of image processing since you will be able to detect edges, corners, and even faces! Not only…
Apr 8, 2023
kakamana
4 min

Filters, Contrast, Transformation and Morphology

python
datacamp
machine learning
image processing
We will teach you how to detect object shapes using edge detection filters, enhance medical images with contrast enhancement, and even enlarge pictures five times their…
Apr 8, 2023
kakamana
5 min

Going Deeper convolutions in keras

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
Convolutional neural networks gain a great deal of power when they are constructed with multiple layers (deep networks). You will learn how to stack multiple convolutional…
Apr 8, 2023
kakamana
5 min

Image Processing With Neural Networks

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
In order to learn, convolutional neural networks use the data represented in images. We will learn how to use Keras to train a neural network to classify objects that appear…
Apr 8, 2023
kakamana
5 min

Image restoration, Noise, Segmentation and Contours

python
datacamp
machine learning
image processing
You have done some very cool things with your image processing skills so far. In this chapter, you will learn how to apply image restoration to remove unwanted objects…
Apr 8, 2023
kakamana
6 min

Introducing Image Processing and scikit-image

python
datacamp
machine learning
image processing
Learn how to process digital image structures! NumPy and Scikit-image can be used to extract data, transform images, and analyze them. In just a few lines of code, you will…
Apr 8, 2023
kakamana
5 min

Multiple Outputs

python
datacamp
machine learning
deep learning
tensorflow
keraas
neural network
You will build neural networks with multiple outputs in this chapter, which can be used to solve regression problems with multiple targets. Additionally, you will build a…
Apr 8, 2023
kakamana
5 min

Multiple Inputs: 3 Inputs (and Beyond!)

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
You will learn how to extend your 2-input model to 3 inputs, and how to use Keras’ summary and plot functions to understand the parameters and topology of your neural…
Apr 8, 2023
kakamana
5 min

Understanding and Improving Deep Convolutional Networks

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
The use of neural networks for training can be improved in a number of ways. We will discuss approaches to improving convolutional neural networks in this chapter as well as…
Apr 8, 2023
kakamana
5 min

Using Convolutions

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
Convolutions are the basic building blocks of convolutional neural networks. You will learn how convolutions operate on image data in this chapter. Additionally, you will…
Apr 8, 2023
kakamana
5 min

The Keras Functional API

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
This chapter introduces you to the basics of Keras’ functional API. By using functional building blocks, you will construct a simple functional network, fit it to data, and…
Apr 7, 2023
kakamana
6 min

Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
This chapter focuses on building two-input networks using categorical embeddings for high-cardinality data, shared layers for re-usable building blocks, and merged layers…
Apr 7, 2023
kakamana
5 min

Advanced Model Architectures

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
Now is the time to learn more about advanced architectures! As you build a network that predicts the next word in a sentence, you will learn more about recurrent neural…
Apr 6, 2023
kakamana
8 min

Improving Your Model Performance

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
You have trained a great deal of models in the previous chapters. As your models are trained, you will learn how to interpret learning curves. Additionally, you will be able…
Apr 6, 2023
kakamana
7 min

Introducing Keras

python
datacamp
machine learning
deep learning
keras
neural network
The purpose of this first chapter is to introduce you to neural networks, to understand what kinds of problems they can solve, and when they should be used. Moreover, you…
Apr 6, 2023
kakamana
5 min

Building deep learning models with keras

python
datacamp
machine learning
deep learning
keras
Throughout this chapter, you will build deep learning models for both regression and classification using the Keras library. In this chapter, you will learn about the…
Apr 5, 2023
kakamana
5 min

Going Deeper

python
datacamp
machine learning
deep learning
tensorflow
keras
neural network
Upon completion of this chapter, you will be able to solve binary, multi-class, and multi-label problems using neural networks. All of this can be accomplished by solving…
Apr 5, 2023
kakamana
7 min

Fine-tuning keras models

python
datacamp
machine learning
deep learning
keras
There will be a discussion on some basic NLP concepts, such as word tokenization and regular expressions for parsing text. We will also cover how to handle non-English…
Apr 4, 2023
kakamana
6 min

Optimizing a neural network with backward propagation

python
datacamp
machine learning
deep learning
neural network
You will learn how to optimize the predictions generated by your neural networks. One of the most important techniques in deep learning is called backward propagation. In…
Apr 4, 2023
kakamana
7 min

Basics of deep learning and neural networks

python
datacamp
machine learning
deep learning
neural network
It is in this chapter that you will gain an understanding of the fundamental concepts and terminology used in deep learning, as well as why these techniques are so powerful…
Apr 3, 2023
kakamana
4 min

High Level APIs

python
datacamp
machine learning
tensorflow
keras
You will use high-level APIs in TensorFlow 2 to train a sign language letter classifier in the final chapter. To train, validate, make predictions with, and evaluate models…
Apr 1, 2023
kakamana
6 min

Introduction to TensorFlow

python
datacamp
machine learning
tensorflow
To build advanced models in TensorFlow 2, you must first understand the basics. The purpose of this chapter is to teach you how to define constants, variables, add and…
Apr 1, 2023
kakamana
5 min

Neural Networks

python
datacamp
machine learning
tensorflow
neural network
As you learned in the previous chapters, TensorFlow 2 was used to build models. With the help of those same tools, you will build, train, and make predictions using neural…
Apr 1, 2023
kakamana
8 min

Basic features and readability scores

python
datacamp
machine learning
nlp
feature engineering
You will learn how to calculate basic features such as word count, character count, average word length, and special characters (such as Twitter hashtags and mentions). In…
Mar 30, 2023
kakamana
5 min

N-Gram models

python
datacamp
machine learning
nlp
feature engineering
Learn about n-gram modeling and use it to perform sentiment analysis on movie reviews
Mar 30, 2023
kakamana
5 min

TF-IDF and similarity scores

python
datacamp
machine learning
nlp
feature engineering
The cosine similarity score and TF-IDF weights will be computed between two vectors in this course. Using these concepts, you will create a movie recommendation system and a…
Mar 30, 2023
kakamana
6 min

Building fake news classifier

python
datacamp
machine learning
nlp
supervised machine learning
To build a “fake news” detector, you will combine what you have learned with some supervised machine learning. The first step will be to learn the basics of supervised…
Mar 24, 2023
kakamana
4 min

Linear models

python
datacamp
machine learning
tensorflow
linear model
The purpose of this chapter is to introduce you to TensorFlow 2, where you will learn how to build, solve, and make predictions using models. As part of this assignment, you…
Mar 24, 2023
kakamana
6 min

Named-entity recognition

python
datacamp
machine learning
nlp
Throughout this chapter, you will learn how to use pre-trained models on English and non-English texts to identify who, what, and where in your texts. This course introduces…
Mar 24, 2023
kakamana
4 min

Regular expressions & word tokenization

python
datacamp
machine learning
nlp
There will be a discussion on some basic NLP concepts, such as word tokenization and regular expressions for parsing text. We will also cover how to handle non-English…
Mar 24, 2023
kakamana
4 min

Simple topic identification

python
datacamp
machine learning
nlp
tf-idf
By using basic NLP models, you will be able to identify topics from any text you encounter in the wild. You will experiment and compare two simple methods: bag-of-words and…
Mar 24, 2023
kakamana
4 min

Text preprocessing, POS tagging and NER

python
datacamp
machine learning
nlp
feature engineering
With the spaCy library, you will learn how to perform text cleaning, part-of-speech tagging, and named entity recognition by using tokenization and lemmatization. By…
Mar 24, 2023
kakamana
5 min

Basic modeling in scikit-learn

python
datacamp
machine learning
models
Validating models requires an understanding of how they are created and used. In this brief summary, you will learn how to run regression and classification models in…
Mar 22, 2023
kakamana
5 min

Cross validation in modeling

python
datacamp
machine learning
models
Holdout sets are an excellent starting point for model validation. It is important to note, however, that using one train and one test set is often not sufficient. When…
Mar 22, 2023
kakamana
5 min

Selecting best model with hyperparameter tunning

python
datacamp
machine learning
models
Model validation techniques were the focus of the first three chapters. The purpose of chapter 4 is to apply these techniques, specifically cross-validation, while learning…
Mar 22, 2023
kakamana
5 min

Validation basic for modeling

python
datacamp
machine learning
models
In this section, we will focus on the basics of model validation. To build the foundation for the techniques of K-Fold and Leave-One-Out validation practiced in chapter…
Mar 22, 2023
kakamana
5 min

Confirming to statistical assumptions

python
datacamp
feature engineering
machine learning
statistical analysis
In this chapter, we’ll look at how the underlying distribution of our data affects our machine learning pipeline. We’ll learn how to deal with skewed data and how outliers…
Mar 19, 2023
kakamana
5 min

Creating Features - Feature Engineering for Machine Learning

python
datacamp
feature engineering
machine learning
This course will teach us the basics of feature engineering and how to use it. We’ll load, explore, and visualize a survey response dataset, and we’ll see what types of data…
Mar 19, 2023
kakamana
4 min

Dealing with messy data

python
datacamp
feature engineering
machine learning
data wrangling
This chapter will introduce us to messy, incomplete data. In this lesson, we’ll learn how to find missing values in our data and explore multiple approaches to dealing with…
Mar 19, 2023
kakamana
5 min

Dealing with text data

python
datacamp
feature engineering
machine learning
data wrangling
Finally, we’ll look at ways to engineer columnar features from unstructured text data. How different approaches might affect how much context is extracted from a text, and…
Mar 19, 2023
kakamana
5 min

Bringing it all together - Network analysis

python
datacamp
network analysis
machine learning
NetworkX
We’ll consolidate everything you’ve learned through an in-depth case study of GitHub collaborator network data. This is a great example of real-world social network data…
Mar 11, 2023
kakamana
2 min

Important nodes - Network analysis

python
datacamp
network analysis
machine learning
NetworkX
This course will introduce us to the advanced concepts of network analysis and the basics of path finding algorithms while identifying nodes that are important in a network.…
Mar 11, 2023
kakamana
3 min

Introduction to networks

python
datacamp
network analysis
machine learning
NetworkX
During this course, we will explore a dataset of Twitter networks to learn about fundamental concepts in network analytics. We will also learn about NetworkX, a library for…
Mar 11, 2023
kakamana
3 min

Structures - Network analysis

python
datacamp
network analysis
machine learning
NetworkX
We will learn how to find interesting structures within network data by studying concepts such as cliques, communities, and subgraphs. This exercise will leverage your…
Mar 11, 2023
kakamana
4 min

Fuzzy Regression Discontinuity Design: An Introduction

python
causal inference
MADS
University Of Michigan
statistics
regression discontinuity
This article includes:
Feb 27, 2023
kakamana
6 min

Regression Discontinuity in Causal Inference: An Introduction

python
causal inference
MADS
University Of Michigan
statistics
regression discontinuity
As part of causal inference, statistical techniques are utilized to identify causal relationships between variables. Regression analysis is an important method for causal…
Feb 27, 2023
kakamana
5 min

Sharp Regression Discontinuity Design: An Introduction

python
causal inference
MADS
University Of Michigan
statistics
regression discontinuity
A Sharp Regression Discontinuity Design (SRDD) employs regression discontinuity to estimate causal effects. When a threshold exists in the outcome variable, SRDD is used.…
Feb 27, 2023
kakamana
5 min

Predicting Time Series Data

python
datacamp
machine learning
time series
How you choose and construct a model for predicting patterns from data over time requires special consideration. Predictive modeling for time series data is discussed in…
Jan 27, 2023
kakamana
6 min

Validating and Inspecting Time Series Models

python
datacamp
machine learning
time series
Once you’ve got a model for predicting time series data, you need to decide if it’s a good or a bad model. This chapter coves the basics of generating predictions with…
Jan 27, 2023
kakamana
8 min

Time Series and Machine Learning Primer

python
datacamp
machine learning
time series
A brief introduction to the basics of machine learning, time series data, and the intersection between the two
Jan 24, 2023
kakamana
3 min

Time Series as Inputs to a Model

python
datacamp
machine learning
time series
To include time series in your machine learning pipeline, you use them as features in your model. We will briefly covers the common features that are extracted from time…
Jan 24, 2023
kakamana
6 min

Feature Engineering

python
datacamp
machine learning
feature engineering
We will cover a variety of aspects of feature engineering in this section, including how to use the features already present in a dataset to create new, more useful…
Jan 23, 2023
kakamana
3 min

Introduction to Data Preprocessing

python
datacamp
machine learning
EDA
In order to understand exactly what data preprocessing is all about, you will need to take the first steps in your preprocessing journey, which includes exploring data types…
Jan 23, 2023
kakamana
3 min

Putting It All Together

python
datacamp
machine learning
feature engineering
PCA
Now that we have explored all about preprocessing, lets try these techniques out on a dataset that records information on UFO sightings.
Jan 23, 2023
kakamana
3 min

Selecting Features for Modeling

python
datacamp
machine learning
feature engineering
PCA
We are going to learn how to create a few different techniques to evaluate the most important features from your dataset. we will learn how to eliminate redundant features…
Jan 23, 2023
kakamana
4 min

Standardizing Data

python
datacamp
machine learning
EDA
Standardizing data is all about making sure that your data fits the assumptions that the model is making about the distribution or amount of features you have. Standardizing…
Jan 23, 2023
kakamana
3 min

Exploring High Dimensional Data

python
datacamp
feature engineering
machine learning
dimension
It will introduce us to dimensionality reduction and explain why and when it is important. It will also teach us the difference between feature selection and feature…
Jan 22, 2023
kakamana
3 min

Feature Extraction

python
datacamp
feature engineering
machine learning
dimension reduction
PCA
Principal Component Analysis (PCA), the most widely used dimensionality reduction algorithm, is covered briefly here. We will learn how and why this algorithm is so…
Jan 22, 2023
kakamana
4 min

Feature Selection I - Selecting for Feature Information

python
datacamp
feature engineering
machine learning
dimension reduction
As we progress through feature selection, we’ll learn how dimensionality reduction can help us overcome its curse. We’ll be introduced to a variety of techniques for…
Jan 22, 2023
kakamana
3 min

Feature Selection II - Selecting for Model Accuracy

python
datacamp
feature engineering
machine learning
dimension reduction
We’ll explore how to use models to identify the most important features in a dataset in order to predict certain targets. We then concludes with a lesson in which we will…
Jan 22, 2023
kakamana
4 min

Classification with XGBoost

python
datacamp
classification
machine learning
XGBoost
The fundamental idea behind XGBoost—boosted learners—will be introduced to you in this module. After gaining an understanding of how XGBoost works, we’ll apply it to solving…
Jan 21, 2023
kakamana
6 min

Fine-tuning your XGBoost model

python
datacamp
hyperparameters
machine learning
XGBoost
You will learn how to adjust XGBoost’s parameters and how to tune them efficiently so that you can supercharge the performance of your models
Jan 21, 2023
kakamana
5 min

Regression with XGBoost

python
datacamp
regression
machine learning
XGBoost
After a brief review of supervised regression, you’ll apply XGBoost to the regression task of predicting house prices in Ames, Iowa. Aside from learning how XGboost can…
Jan 21, 2023
kakamana
6 min

Using XGBoost in pipelines

python
datacamp
hyperparameters
machine learning
XGBoost
pipeline
Get more out of your XGBoost skills with two end-to-end machine learning pipelines using your models. You’ll learn how to tune the most important XGBoost hyperparameters…
Jan 21, 2023
kakamana
6 min

Applying logistic regression and SVM

python
datacamp
logistic regression
machine learning
SVM
We will learn the basics of applying logistic regression and support vector machines (SVMs) to classification problems. You’ll use the scikit-learn library to fit…
Jan 18, 2023
kakamana
2 min

Introduction to Hypothesis Testing

python
datacamp
statistics
machine learning
hypothesis
We will walk you through the steps of creating a one sample proportional test so that you will be able to better understand how hypothesis tests work and what problems they…
Jan 18, 2023
kakamana
3 min

Logistic regression

python
datacamp
linear classifier
logistic regression
machine learning
SVM
We will discover the conceptual framework behind logistic regression and SVMs. This will let us delve deeper into the inner workings of these models.
Jan 18, 2023
kakamana
4 min

Loss function

python
datacamp
logistic regression
linear classifier
machine learning
SVM
We will discover the conceptual framework behind logistic regression and SVMs. This will let us delve deeper into the inner workings of these models.
Jan 18, 2023
kakamana
2 min

Regression

python
datacamp
logistic regression
machine learning
supervised
We will be introduced to regression, and build models to predict sales values using a dataset on advertising expenditure. We will learn about the mechanics of linear…
Jan 18, 2023
kakamana
5 min

Support Vector Machines

python
datacamp
linear classifier
machine learning
SVM
We will learn all about the details of support vector machines. We will explore about tuning hyperparameters for these models and using kernels to fit non-linear decision…
Jan 18, 2023
kakamana
3 min

Sampling Distribution

python
datacamp
statistics
machine learning
sampling
distribution
We will discover how to quantify the accuracy of sample statistics using relative errors, and measure variation in your estimates by generating sampling distributions.
Jan 14, 2023
kakamana
3 min

Assessing model fit

python
datacamp
statistics
machine learning
linear regression
What questions to ask your model to determine its fit. We will discuss how to quantify how well a linear regression model fits, how to diagnose problems with the model using…
Jan 13, 2023
kakamana
4 min

Sampling Methods

python
datacamp
statistics
machine learning
sampling
It’s time to get hands-on and perform the four random sampling methods in Python: simple, systematic, stratified, and cluster.
Jan 13, 2023
kakamana
3 min

Simple Logistic Regression Modeling

python
datacamp
statistics
machine learning
linear regression
logistic regression
Get a better understanding of logistic regression models. We will analyze real-world data to predict the likelihood of a customer closing their bank account in terms of…
Jan 13, 2023
kakamana
6 min

Introduction to sampling

python
datacamp
statistics
machine learning
sampling
Get a better understanding of what sampling is and why it is so powerful. Additionally, We will learn about the problems associated with convenience sampling and what the…
Jan 8, 2023
kakamana
2 min

Predictions and model objects in linear regression

python
datacamp
statistics
machine learning
linear regression
logistic regression
This article explores how linear regression models can be used to predict Taiwanese house prices and Facebook advert clicks. Our regression skills will also be developed…
Jan 8, 2023
kakamana
3 min

Simple Linear Regression Modeling

python
datacamp
statistics
machine learning
linear regression
logistic regression
We will learn the basics of this popular statistical model, what regression is, and how linear and logistic regressions differ. We’ll then learn how to fit simple linear…
Jan 8, 2023
kakamana
5 min

Correlation in a nutshell

python
datacamp
statistics
correlation
In this article we will explore basically a linear relationship between two variables, its possible quantification (magnitude & direction). We will also touch high level of…
Jan 7, 2023
kakamana
2 min

Classification

python
datacamp
classification
machine learning
supervised
We will explore how to solve classification problems using supervised learning techniques, which include splitting data into training and test sets, fitting a model…
Jan 6, 2023
kakamana
6 min

Correlation and Experimental Design

python
datacamp
statistics
correlation
We will explore how to quantify the strength of a linear relationship between two variables, and explore how confounding variables can affect the relationship between two…
Jan 6, 2023
kakamana
7 min

Distribution (pdf, cdf) of iris data

python
statistics
distribution
Lets explore distribution functions pdf and cdf using Iris data set
Jan 6, 2023
kakamana
1 min

Fine Tunning Model

python
datacamp
machine learning
supervised
After training models, you’ll learn how to assess them in this chapter. You’ll learn how to analyze classification model performance using scikit-learn by using several…
Jan 6, 2023
kakamana
7 min

Preprocessing and Pipelines

python
datacamp
machine learning
supervised
Learn how to impute missing values, convert categorical data to numeric values, scale data, evaluate multiple supervised learning models simultaneously, and build pipelines…
Jan 6, 2023
kakamana
6 min

Random Numbers and Probability

python
datacamp
statistics
distribution
This Random Numbers and Probability is part of Datacamp course: Introduction to Statistic in Python
Dec 27, 2022
kakamana
5 min

Summary Of Statistics

python
datacamp
statistics
Datacamp course: Introduction to Statistic in Python
Dec 27, 2022
kakamana
3 min
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