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When Do We Need Machine Learning?

When Do We Need Machine Learning?

In this article, I will introduce you to a very important concept for machine learning practitioners: when do we need machine learning. It’s one of those basic issues that every computer science student faces when moving from basic computing practices to machine learning. If you are one of those people who does not know when we should use programming and when do we use machine learning algorithms, I hope by the end of this article you will understand all about when do we use machine learning. Also, Read – Predict Car Prices with Machine Learning. So What is Machine Learning?…

Predict Car Prices with Machine Learning

Predict Car Prices with Machine Learning

In this article, I am going to walk you through how we can train a model that will help us predict car prices with Machine Learning using PyTorch. The dataset I’m going to use here to predict car prices is tabular data with the prices of different cars regarding the other variables, the dataset has 258 rows and 9 columns, the variable we want to predict is the selling price of the cars. What is PyTorch? PyTorch is a library in Python which provides tools to build deep learning models. What python does for programming PyTorch does for deep learning.…

Maths for Machine Learning

Maths for Machine Learning

Machine learning is about designing algorithms that automatically extract valuable information from data. The emphasis here is on ‘automatic’, that is, machine learning is about general-purpose methodologies that can be applied to many sets of data while producing something meaningful. In this article, I will take you through why you need to learn some maths for machine learning and some important topics of maths that you need to learn. Why Maths for Machine Learning? Because machine learning is inherently data-driven, data acts as the heart of machine learning algorithms. The goal of machine learning is to design general-purpose methodologies to…

Python Interview Questions

Python Interview Questions

Python is now one of the most popular and skilful languages in programming domain. In this article, I will take you through some of the most important Python interview questions you need to know. To sit in an interview you must be familiar with most of the basics of Python. If you have covered the basics with some python projects along then it’s the python interview question that you must be searching for. But before I dive into the python interview questions if you have still not worked on any Python project then I suggest you start with it soon…

Model Validation in Machine Learning

Model Validation in Machine Learning

In machine learning, model validation is a very simple process: after choosing a model and its hyperparameters, we can estimate its efficiency by applying it to some of the training data and then comparing the prediction of the model to the known value. In this article, I’ll introduce you to a very naive approach to model validation and the reasons for its failure, before exploring the use of exclusion sets and cross-validation for more robust model evaluation. Also, Read – Machine Learning Projects for Healthcare. Model validation the wrong way I will start by demonstrating the naive approach to validation…

Machine Learning for Healthcare

Machine Learning for Healthcare

Electronically stored medical imaging data is plentiful and Machine Learning algorithms can be fed with this type of dataset, to detect and uncover patterns and anomalies. In this article, I will introduce you to five machine learning projects for healthcare. Machines and algorithms can interpret imaging data just as a highly trained radiologist could identify suspicious spots on the skin, lesions, tumours and bleeding in the brain. The use of machine learning tools and platforms to help radiologists is therefore poised to grow exponentially. Also, Read – Analyze Call Records with Machine Learning using Google Cloud Platform. Machine Learning Projects…

Analyze Call Records with Machine Learning

Analyze Call Records with Machine Learning

For most businesses, the story generally goes as follows. A customer calls to complain, praise or ask for help, then the call is recorded for further training or assessment, then the recording is usually chosen at random, listened to by someone, and reviewed with the representative of the customer. customer service. In this article, I’ll walk you through how we can analyze call records with Machine Learning. To Analyze the call records can take anywhere from an hour to a week after a customer hangs up. During this time, a lot can go wrong. Compliance issues and poor service could…

Physical Computing with Python

Physical Computing with Python

One of the reasons I want you to learn about physical computing is because small computers doing physical activities are all around you. And we mean everywhere. Go up to your kitchen. Look around you. Your refrigerator has a computer, maybe two or three if it has a screen. Your mixer has a computer. In this article, I will explain how we can use the power of python for physical computing. Your oven is equipped with a computer. Your microwave is equipped with a computer. If you use Phillips Hue lights in your home, your bulbs come with a computer.…

Python Lists

Python Lists

Python Lists are the most flexible and ordered collection object. Lists can contain any type of data types: numbers, strings, and even lists. The best way to understand list in python is to understand by using it. A list can be easily created with [ ]. Now let’s do some operation to understand the List in python. Basic Python Lists Operations Lists are sequences in Python, we use it to store data of any data type. It is very easy and flexible to use. Now let’s start with the very basic functions of lists. Also, Read – Physical Computing with…

How to Choose an Algorithm in Machine Learning

Choose Algorithm in Machine Learning

For any given machine learning problem, many algorithms can be applied and several models can be generated. A spam detection classification problem, for example, can be solved using a variety of models, including naive Bayes, logistic regression, and deep learning techniques like LSTMs. In this article, I will tell you how to choose a machine learning algorithm for a particular task out of so many algorithms. Having a plethora of options is good, but deciding which model to implement in production is crucial. Although we have multiple performance metrics to evaluate a model, it doesn’t make sense to implement every…

Count Rainy Days with Python

Count Rainy Days with Python

In this article, I will walk you through a numerical computational task with Python to count rainy days with python. Imagine you have a data series that represents the amount of precipitation each day for a year in a given city. For this task of numerical computing with python to count rainy days within a year, I will start this off by loading the data, that you can download from here: Also, Read – NLP Projects for Machine Learning. (365,) The table contains 365 values, giving the daily precipitation in inches from January 1 to December 31, 2014. Before we…

NLP Projects for Machine Learning

NLP Projects for Machine Learning

Natural Language Processing (NLP) consists of developing applications and services capable of understanding human languages. Some practical examples of NLP are speech recognition, for example, Google voice search, understanding content or analyzing feelings, etc. In this article, I will take you through some very useful NLP Projects for Machine Learning. NLP Projects NLP for Other Languages  Natural Language Processing (NLP) is a great task in Machine Learning to work with languages. However, you must have seen everyone working with only in the English language while working on a task of NLP. So what about other languages that we have. Here…

JSON in Python

JSON in Python

In this article, I will introduce you to JSON in Python. At the end of this article, you are going to learn what JSON is, why it exists, why people use it, and finally how to use the power of python for JSON. As a data scientist, programmer, or even a machine learning practitioner, it’s important that you understand what JSON is and how to use it. I’m sure you’ll find plenty of applications there once you get the hang of it. Also, Read – 9 Computer Vision Projects for Machine Learning. What is JSON in Python? JSON stands for…

Computer Vision Projects

Computer Vision Projects with Python

Computer vision is a field of machine learning that processes images to solve real visual problems. In this article, I’m going to introduce you to some very useful computer vision projects and tasks that will help you boost your portfolio. What is Computer Vision? Humans have no problem identifying objects and the environment around them. However, it is not so easy for computers to identify and distinguish between the various models, visuals, images and objects in the environment. This is where computer vision comes in handy. In the simplest terms, computer vision is the discipline in a broad field of…

What is Transfer Learning in Machine Learning?

What is Transfer Learning in Machine Learning?

Humans have an inherent ability to transfer knowledge between tasks. What we acquire as knowledge while learning a task, we use it in the same way to solve related tasks. The more the tasks are linked, the easier it is for us to transfer or use our knowledge in a cross-manner. This is the idea behind Transfer Learning in Machine Learning. In this article, I will explain what transfer learning is. What is Transfer Learning? Until now, conventional machine learning and deep learning algorithms have traditionally been designed to operate in isolation. These algorithms are trained to solve specific tasks.…

Machine Learning Roadmap

Machine Learning Roadmap

In this article, I will take you through a complete Machine Learning Roadmap to become an expert in Machine Learning. If you are a beginner or a practitioner of machine learning, it means that you must have a good idea of ​​what machine learning is and you must know the benefits of applying machine learning to solve trade issues. On top of that, the most important thing you need to know in the process is how to become a machine learning expert. So in this article, I’m going to present you a complete roadmap for becoming a machine learning expert.…

API with Python

API with Python

Have you ever heard of the word API and wondered what it is exactly? Got a vague idea, but want to know more about what you could do with an API and how you could create one? In this article, I will walk you through how we can build an API with Python. What is an API? API stands for Application Programming Interface. Simply put, APIs simply allow applications to communicate with each other. When people talk about APIs, they sometimes generalize to mean a publicly available web API that returns data, likely in JSON or XML format. The API…

Machine Learning for Startups

Machine Learning for Startups

Machine learning is becoming a fundamental need for every business these days and plays a major role in differentiating your startup from others. Unfortunately, most startups underestimate how difficult and expensive implementing machine learning can be. Here are the guidelines I follow for successfully integrating machine learning for startups while they are still in their infancy. So What is Machine Learning? Machine learning refers to one aspect of this goal, in particular, algorithms and processes that learn in the sense of being able to generalize past data and experiences in order to predict future outcomes. Fundamentally, machine learning is a…

Send Emails with Python

Send Emails with Python

Sometimes we can be in a situation where we need to send emails to multiple people in a personalized way. Although these emails follow the same format, the information they contain varies from recipient to recipient. In this article, I will explain to you how we can send emails with Python. Sending emails manually takes time and there is a lot of room for error. Python allows us to automate this process very easily, let’s see how we can send emails with Python. Also, Read – Most Important Python AutoML Libraries. How To Send Emails with Python? As the python…

Python AutoML Libraries

Python AutoML Libraries

Automated machine learning, also known as AutoML, is an emerging field in which the process of building machine learning models to model data is automated. AutoML can make modelling easier and more accessible for everyone. In this article, I’ll walk you through which Python AutoML libraries you should start practising to stay ahead of the competition. Python AutoML Libraries You Should Know Here are the four Python AutoML Libraries that every machine Learning practitioner should know: Also, Read – Will AutoML Replace Data Science Jobs? auto-sklearn auto-sklearn is an automated machine learning toolkit that integrates seamlessly with the standard sklearn…

Will AutoML Replace Data Science Jobs?

Will AutoML Replace Data Science Jobs?

If you are a Machine Learning Practitioner, you must be having this question these days that will AutoML replace Data Science Jobs or not? Now, this is a good question if you are dedicated to your practice and you will feel demotivated if a concept like AutoML will become an enemy for your future. In this article, I will answer this question for you that will AutoMl Replace Data Science Jobs? What is AutoML? As the name suggests, AutoML is an area of ​​machine learning concerned with automating the repetitive tasks of the machine learning process. AutoML aims to automate…

Colour Recognition with Python

Colour Recognition with Python

In this article, I’ll walk you through a colour recognition task with Python. This process is also known as colour detection. We are going to create a basic application that will help us detect colours in an image. The program will also return the RGB values ​​of the colours, which is useful. Many graphic designers and web designers will understand how useful RGB values ​​can be. Building a colour recognition tool is a great project to get started with Computer Vision. Also, Read – Creating a 3D Video with Python. Colour Recognition with Python using OpenCV If you’ve never heard…

3D Video with Python

In this article, I will take you through an excellent technique to create a 3D video with python by using the matplotlib package. But before learning to create a 3D video with python, I would suggest you learn how to create 3D plots with python from here. 3D Video with Python using Matplotlib First, I’ll create a simple 3D contour plot with matplotlib: Also, Read – How to use Machine Learning in Marketing? The code above will give you a digit without an axis because we are declaring axis3don = False. We cannot hide the panel and grid colour, but we…

Machine Learning in Marketing

Machine Learning in Marketing

In B2B marketing, companies use customer relationship management (CRM) software such as Salesforce, Oracle, and SugarCRM to maintain contact records of business partners who maintain key roles in decision making and purchasing. This data can be used in machine learning environments with marketing analysis software to map the effectiveness of advertising campaigns in specific markets. The inclusion of personalized events such as outbound calls and email newsletters in the sales channel can be recorded in charts to analyze future purchase results. Also, Read – NumPy Broadcasting in Python. Attendance at trade shows and promotional events is noted by timestamps in…

NumPy Broadcasting in Python

NumPy Broadcasting in Python

In Python, NumPy Broadcasting describes how arithmetic works between arrays of different shapes. This is a very powerful feature, but one that can be easily misunderstood, even by experienced users. In this article, I will introduce you to NumPy Broadcasting in Python. NumPy Broadcasting The simplest example of Numpy Broadcasting occurs when combining a scalar value with an array: Also, Read – Image Features Extraction with Machine Learning. [0 1 2 3 4][ 0 4 8 12 16] We say here that the scalar value 4 has been broadcast to all other elements of the multiplication operation. For example, we…

image features extraction

Image Features Extraction with Machine Learning

A local image characteristic is a tiny patch in the image that is indifferent to the image scaling, rotation, and lighting change. It’s like the tip of a tower or the corner of a window in the image below. In this article, I will walk you through the task of image features extraction with Machine Learning. Unlike a random point on the background of the image above, the tip of the tower can be accurately detected in most images of the same scene. It is geometric and photometrically invariant. Also, Read – A/B Testing in Machine Learning. Characteristics of Good…

A/B Testing in Machine Learning

AB Testing in Machine Learning

AB Testing refers to a randomized controlled experiment designed to understand how system variants affect metrics. Most major websites today run hundreds or even thousands of AB tests simultaneously, as different product groups seek to optimize for different metrics. In this article, I’ll walk you through what AB testing is and how we can use it in Machine Learning. How does AB Testing work? The general process for AB Testing is to randomly divide the user population into two groups, A and B, and show each group a different variant of the system in the analysis (for example, a spam…

Lambda in Python

Lambda in Python

Besides the def statement, Python also provides a form of expression that generates function objects. Due to its similarity to a Lisp language tool, it is called lambda. In this article, I will introduce you to the Lambda function in Python. What is Lambda in Python? Like def, the Lambdas expression creates a function to be called later but returns the function instead of assigning it to a name. Because of this lambdas are like anonymous functions in python. In practice, they are often used to insert a function definition or to delay the execution of a piece of code.…

SARIMA in Machine Learning

SARIMA in Machine Learning

In Machine Learning, a seasonal autoregressive integrated moving average (SARIMA) model is a different step from an ARIMA model based on the concept of seasonal trends. In this article, I will introduce you to the SARIMA model in machine learning. What is the SARIMA Model? Seasonal variations of the time series can take into account periodic models, allowing more accurate predictions. Seasonal ARIMA (SARIMA) defines both a seasonal and a non-seasonal component of the ARIMA model, allowing periodic characteristics to be captured. Also, Read – How To Launch Your Machine Learning Model? By choosing an appropriate forecasting model, always visualize…

Launch a Machine Learning Model

Launch a Machine Learning Model

Great, you’ve got approval to launch a machine learning model. Now you need to prepare your solution for production (e.g. tweaking the code, writing documentation and testing, etc.). Then you can launch your machine learning model in your production environment. How To Launch a Machine Learning Model? One way to launch a machine learning model is to save the trained model (for example, using joblib), including the entire preprocessing and prediction pipeline, and then load that trained model into your production environment. Also, Read – Word Embeddings in Machine Learning. To save a model using Joblib: And then to load…

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About Me

Hi, I am Aman Kharwal. I am a programmer from India, and I am here to guide you with Machine Learning for free. I hope you will learn a lot in your journey towards ML and AI with me.

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