AlgoDaily - Machine Learning

In this series, AlgoDaily presents the hottest topic of this era: machine learning. Throughout this series, you will start from scratch and slowly learn basic to advanced machine learning algorithms. We will walk you through several popular machine learning frameworks like NumPy, Scikit-learn, TensorFlow, Keras, etc. So get ready to start your awesome ride to the world where computers are treated like children and we teach them many things with real-world data.

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1. LESSON

Introduction to Machine Learning

In this series, AlgoDaily presents machine learning. You will start from scratch and slowly learn basic and then advanced algorithms in machine learning. We will walk you through many popular machine learning frameworks such as NumPy, Scikit-learn, TensorFlow, and Keras. You will also learn how to understand and manipulate...

43 minutes Mark Completed

2. LESSON

Machine Learning Interview Questions

Machine learning (ML) is a hot topic these days, so it's no wonder that many people want to orient their careers towards this promising field. Therefore, if you want to get a machine learning job, then make sure you review these common ML questions and topics to prepare yourself for a successful interview. AI vs. ML vs. D...

21 minutes Mark Completed

3. LESSON

Introduction to Probability and Statistics

“Data Scientist is a person who is better at statistics than any programmer and better at programming than any statistician.” This definition, given by Josh Wills, is one of the most powerful definitions of a data scientist so far. ![](https://storage.googleapis.com/algodailyrandomassets/curri...

19 minutes Mark Completed

4. LESSON

Introduction to Data Analysis

What is Data Analytics Data analysis aids the company’s success and growth by telling you where to focus your efforts and where to make changes. Most businesses collect large amou...

20 minutes Mark Completed

5. LESSON

Basic Classification and Machine Learning

Introduction As we all know, the regression and classification algorithms are two types of supervised machine Learning algorithms. Regression a...

21 minutes Mark Completed

6. LESSON

All About NumPy and Pandas

NumPy and Pandas are the most popular libraries for numeric computation in Python. NumPy is actually so popular that there are ongoing debates arguing that the library should be built into Python itself rath...

36 minutes Mark Completed

7. LESSON

Into the World of Machine Learning

In this lesson, we will build our first machine learning algorithm using NumPy. You will also learn about several types of classes and common keywords in machine learning. By the end of the lesson, you will begin to understand what machine learning is really like. Intuition Let's build a program that guesses what number...

42 minutes Mark Completed

8. LESSON

Hands-on first Machine Learning Algorithm from Scratch

Previously, we have created a program, that behaves almost like a machine learning algorithm. But in this section, we will officially create our first machine learning program. We are going to implement linear regression. Objective Our objective is to predict house prices based on several features of a house. As there...

19 minutes Mark Completed

9. LESSON

Understanding the Data: Statistics

In this lesson, we will get started with some very basic statistical analysis. A statistic of data is just a summary of that data for humans and computers. Imagine you have a medical history of 2 million people from multiple hospitals, and you want to know which disease is worst among a set of diseases. Of course, you cannot go...

34 minutes Mark Completed

10. LESSON

Standardization & Normalization

So you've collected all your data and now it's time to run your machine learning project. In the data you have collected there will be the features which all have two important properties; the unit and the magnitude. For example, the feature 'age', has units of years and the magnitude is the value. ![]...

6 minutes Mark Completed

11. LESSON

Data Visualization

In this lesson, we will introduce two new giant libraries: matplotlib and plotly. There are tons of visualization libraries in python, but matplotlib is the lowest level and most of the other libraries (e.g. seaborn, ggplot, bokeh, etc.) are built only on matplotlib. We are also introducing you to plotly to make yo...

22 minutes Mark Completed

12. LESSON

R Vs Python for Machine Learning

So you're thinking of building a machine learning project, and it's time to decide on a programming language. Although programming languages R and Python offer similar capabilities, they differ in syntax, libraries and community support. Let's take a closer look at the two. ![](https://storage.googleapis.co...

9 minutes Mark Completed

13. LESSON

Advanced Machine Learning Interview Questions

Preparing for a machine learning interview can be challenging and overwhelming. In order to make the process easier for you, we have prepared a list of questions that you might be asked and their answers. You should first go through the more simple [machine learning interview questions](https://algodaily.com/lessons/ml-interview-...

20 minutes Mark Completed

14. LESSON

Machine Learning Made Easy: Scikit-Learn

In this lesson, we will go through some common usages of the powerful and most popular Machine Learning framework, Scikit-Learn. The scikit-Learn library helps all the newcomers to learn more about different Machine Learning practices. It helps the user to achieve the most trivial machine learning tasks in the fewest lines possi...

38 minutes Mark Completed

15. LESSON

Machine Learning Made Easy: Scikit-Learn (Part-2: Unsupervised Learning)

Previously, we have understood the core concepts of supervised machine learning and how to use most of the common implementations of many preprocessing techniques, models, etc. with scikit-learn. In this lesson, we will be covering most approaches and techniques used for unsupervised learning usi...

60 minutes Mark Completed

16. LESSON

Introduction to Neural Networks

In this lesson, we will introduce the hot cake of the field of Machine Learning. Neural Networks are models designed based on our brains. Human brains have about 86 billion cells connected together by synapses. A neural network also has many cells/units that are connected to one another. Whenever an input is given, it is propaga...

31 minutes Mark Completed

17. LESSON

How Do Artificial Neural Networks Work?

How Do Artificial Neural Networks Work Introduction The human brain is extremely complex and is composed of billions of neurons that store and distribute information. The main idea behind the artificial neural network (ANN) is to mimic the behavior of the human brain and be able to “think” and make decisions. Artificial neural networks...

16 minutes Mark Completed

18. LESSON

Introduction to TensorFlow

Those who are continuing from the last lesson (Deep Learning) of this series, you might felt deep learning to be a very difficult concept. I agree with you, deep learning is not that easy if you try to implement it from scratch (reinvent the wheel). But in this lesson, we will walk through the final framework in this series, **T...

40 minutes Mark Completed

19. LESSON

Deep Learning and Computer Vision

In the previous lesson, you were introduced to one of the most popular frameworks for Deep Learning, TensorFlow. In this lesson, we will use TensorFlow to create some popular deep neural networks. In the meantime, you will also learn which deep learning technology should be used with what kind of data, and how you can customize a d...

60 minutes Mark Completed

20. LESSON

Real World Deep Neural Network Examples

After the last lesson, I hope you have got the primer of how Deep Learning and TensorFlow work. In this lesson, we will use some real-life Deep Learning networks, that are used in production for many different applications. The work needed behind creating and training these models is a lot, and you simply cannot go through all the...

67 minutes Mark Completed

21. LESSON

Practical Exercise: Create background removing application for Zoom/Skype

This lesson is an exercise for everyone to apply machine learning to regular applications that we might need. We will create an application that can take the input from the webcam, remove the background from persons (without any green screen), and then transfer it to a virtual device that can be selected by other applications like...

24 minutes Mark Completed

22. LESSON

Anomaly Detection In Machine Learning

Anomaly Detection What is an Anomaly An Anomaly defined as: Something that is different from what is usual or expected. Detecting anomalies has many useful applications. For example anomaly detection enables us to detect cancer in MRI images, detecting credit card fr...

21 minutes Mark Completed

23. LESSON

Introduction to Genetic Algorithms in Python

Genetic Algorithm (GA) is a nature-inspired algorithm that has extensively been used to solve optimization problems. It belongs to the branch of approximation algorithms because it does not guarantee to always find the exact optimal solution; however, it may find a near-optimal solution in a limited time. In this lesson, we will learn the basics o...

36 minutes Mark Completed

24. LESSON

A Guide to A/B Testing

What is A/B Testing? **A/B testing is one of the most essential ideas in data science and the IT sector in general since it is one of the most effective strategies for determining the validity of an...

17 minutes Mark Completed

25. LESSON

Getting to Know Decision Trees

Introduction One of the most powerful and widely used machine learning algorithms used for both classification and regression problems is the decision tree. A huge part...

23 minutes Mark Completed

26. LESSON

How Do Large Language Models Work?

Large language models (LLMs) are a type of artificial intelligence (AI) that are trained on massive amounts of text data. This training allows LLMs to learn the statistical relationships between words and phrases. Once trained, LLMs can be used to generate text, translate languages, write different kinds of creative content, a...

25 minutes Mark Completed

27. LESSON

Univariate, Bivariate, Multivariate Analysis

When we talk about Univariate, Bivariate, Multivariate analysis we are referring to classifications of Exploratory Analysis, which refers to: *‘The critical process of performing initial investigations on data so as to disc...

9 minutes Mark Completed