7th week of 52 weeks

Sajjad RahmanSajjad Rahman
6 min read

Feb - 13

I visited with my friends and then I read ML books. I know the basic term of ML.

In today's world, where data is generated at an unprecedented rate, machine learning has become increasingly important. Machine learning is a subset of artificial intelligence that focuses on the development of algorithms that enable computers to learn from data without being explicitly programmed. In this article, we will explore some of the basic terms and concepts of machine learning.

Data: In machine learning, data is the foundation of everything. It refers to any information that can be processed by a computer. Data can be structured, unstructured, or semi-structured, and can come in various formats such as text, images, audio, and video.

Feature: A feature is an individual measurable property or characteristic of a dataset. These features are used to train machine learning models to make predictions or decisions. The Features can be quantitative (numeric) or categorical (qualitative).

Algorithm: An algorithm is a set of rules or instructions that a machine-learning model follows to learn from data. The goal of an algorithm is to identify patterns and relationships in the data that can be used to make predictions or decisions.

Model: A machine learning model is a mathematical representation of the relationships between the features and the output. The model is trained on a dataset to learn these relationships and can be used to make predictions on new data.

Training: Training is the process of feeding data into a machine-learning model so that it can learn from it. During training, the model adjusts its parameters to minimize the error between the predicted output and the actual output.

Testing: Testing is the process of evaluating the performance of a machine learning model on a new set of data that it has not seen before. The goal of testing is to assess how well the model can generalize to new data.

Supervised Learning: Supervised learning is a type of machine learning where the model is trained on a labeled dataset, where the desired output is known. The model learns to make predictions based on the input data and the known output.

Unsupervised Learning: Unsupervised learning is a type of machine learning where the model is trained on an unlabeled dataset, where the desired output is unknown. The model learns to identify patterns and relationships in the data on its own.

Deep Learning: Deep learning is a subset of machine learning that involves training models on large datasets using neural networks. These neural networks are designed to mimic the structure of the human brain, allowing for more complex and sophisticated learning.

In conclusion, machine learning is a complex field that involves many concepts and terms. Understanding these basic terms and concepts is essential for anyone interested in pursuing a career in this field. With the ever-increasing amount of data being generated every day, the importance of machine learning will only continue to grow in the years to come.

Feb - 14 :

I woke up the late morning as I fixed I never go to University. I passed most of the time by sleeping and then I wrote some code for my flutter project. I face difficulty passing arguments, but after some time I can fix it.

I chat with the chatbot. How to make valentine's day special, it returns to me a motivational speech 😂

Sleep is good, but sleeping too much can be bad for you. If you spent Valentine's Day indoors sleeping and coding, you might be missing out on fun activities and hanging out with people. To feel better, try making a regular sleep schedule and doing some exercise. It can help you have more energy and feel happier. Just remember to take a break from work sometimes and enjoy life!

Feb -15 :

I couldn’t wake up early in the morning as I missed a class. In college the way of reading web courses I did not like. I passed a boring class. After that, my ML lab class teacher came and gave a lecture on the simple terms of ML.

To sum up his lesson, I learned :

Regression: to predict something

Classification: Fix the things has level

Supervised learning: We learn to machine how we should a response

Unsupervised learning: We just put data, machine learning itself.

Feb-16

I woke up early in the morning on my college bus at 8:00 am. I quickly prepared myself so I would not miss the bus.

I took my breakfast from the Mojo near my college. This is the very first computer session lab where the teacher gave us instructions on how to complete the course.

We must go to our local area as we can do fieldwork. we must select a system to use in a software system.

After selecting the idea we must select some questions from them so we can achieve the best idea about their company. Also, teacher warn us that we did not directly ask

How old are you and what is your salary.?

After completing the class, one of my friends and I went to the cafeteria to drink coffee.

Next, I have another class but the teacher is too late as we can not learn much from him.

The next class is about computer graphics where the teacher gave a lecture about "braising ham circle algorithm "

Feb-17

This is Friday. On this day I closed everything. In the afternoon I visited my student's home, where I gave a 4-hour lecture about different widgets of flutter. This is a very important season for me. I love to teach someone.

Feb -18

I woke up in the early morning and was ready to catch my bus. I took my first cup of tea from my college cafeteria and then I went back to class. I went to the web lab class where the teacher give a lecture about margin padding and column-span in HTML, CSS also, gave tasks that is basic HTML and registrations and design with CSS

after that, I have another class that is VLSI, where the teacher took an instant assignment based on a prior class Sir took the assignment as the number of students is less.

Feb -19

As it is the weekend, I woke up late morning and go the market to purchase some things for my house and I am starting to convert some code in my project.

but it gives me errors. I found the error in this

In Flutter, the navigator. pushes and navigator.pushNamed are methods used to navigate between screens or pages in an application . Both methods are used to push a new screen onto the navigation stack, but they work in slightly different ways.

navigator. push is used to push a new screen onto the navigation stack by passing in an instance of the screen widget as a parameter. This method allows you to programmatically create and push a new screen onto the stack, without having to define the screen in the app's route table. Here is an example of using a navigator.push it to push a new screen onto the stack:

Navigator.push(
  context,
  MaterialPageRoute(builder: (context) => NewScreen()),
);

I am going outside with my friends to buy some products from his shop. In the evening I went to my sister's house. When I am back my team starts a meeting that is almost 5 hours long.

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Written by

Sajjad Rahman
Sajjad Rahman

As a Flutter developer, I am constantly learning and trying to implement new concepts into my projects. In addition, I devote time to studying Machine Learning. I have a passion for contributing to open-source projects.