About Me & MyBlog
Software Engineer | Polyglot Programmer | Gym Lover | Cyclist | Algorithm Addict | Programming and Research enthusiast | Life Long Passionate Learner | Love CSE, Backend and DataHi, thanks for your interest on my blog 🙂 I am Syed Ahmed Zaki, Founder of CodeLiftio! This is my blog “Zakilive.Com” for sharing my knowledge and passion with you all.
I was born in a beautiful country of south asia named Bangladesh. I am a Computer Science and Engineering graduate from Daffodil International University. I am passionate, dedicated, hardworking about my tasks and fond of Algorithms, Competitive Programming, Mathematics, Research in data science(Machine Learning, AI, NLP, Deep Learning), bioinformatics and IoT. I also love software engineering. In software development field I prefer Web Application Engineering.
In my Daffodil life I tried to participate in several programming contests(online, onsite, intra etc.) and passed some time in ACM training class for sharpening my logical skills. As an ordinary people it was little bit tough for me alongside with academic pressure, thesis and research paper writing but I love challenges so I always tried to push my limits though still I need to improve a lot in everything but I always trust in this quote “Hard work beats talent”. That quote I have learned from my life through bodybuilding of 6 years since 2012 and after losing 33 KG fat in 4 months from 101 KG I developed my fit physique, so I respectfully believe in this sentence and relate this with CSE field. I also love to learn from my failures. I hate excuses while working professionally and I love trying to finish my work with perfection till the last moment before deadline.
I also love to explore and play with new technologies and try to implement it with innovative ideas. In my university life, I always tried to learn from the basics of CS. So, I have tried to gather Networking to Database Knowledge, OS fundamentals to OOP etc. all fundamental core basics in my skillset in a practical approach.
Alongside with developing some web applications in core php and laravel framework I have also tried to build games with unity3d game engine, built 2 android apps, experimented machine learning with python, data mining with WEKA, AI chatbot, IoT based weather station and some more project works for my undergraduate courses. As I am language and platform agnostic, I enjoyed and learned a lot from all of these works. I also love teamwork. Alongside software engineering and different extra curricular activities I also love teaching. I am also proficient at working with linux and windows based OSes and I feel so lucky if I get chance to contribute in opensource projects. In my linkedin profile you will find more details about me.
However, I am actually a knowledge seeker and life long passionate learner who tries to make his weakness as strength, I was a serious student of all the courses in CS academia that can solve real life problems as I love to explore knowledge in a crafted manner. I love to study books, blogs or whatever philosophically solve my curiosity. For that, I maintain a good collection of various technological, scientific and philosophical books in my small library. Knowledge sharing, analytical thinking, practice and passing the passion of mine with you is one of my motivations for running this blog. I practice to hone my skills with trying to improve my programming and developing skillset day by day and what I learn, I never forget to share here for you.
In my free time I love to do cycling or gym or play racing games in my android phone or watch animated movies and also love to promote positive, fit and healthy lifestyle among people.
Connect with me:
Currently I am working with .NET technologies. If you have any opportunity/business to work with me or any other query kindly say just hi to me at my mail:
[email protected]
Category Archives: Machine Learning
Machine Learning with Python
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# Naive Bayes # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd #importing the dataset dataset=pd.read_csv('clusterincluster.csv'); columns=dataset.iloc[:, [0,1]].values; # here first colon means selecting all rows then after comma means selecting feature/column so manually we can enter 0 and 1 and we can also put -1 to select all rows except the last one as we are making the last one as class #independent variables label=dataset.iloc[:, [2]].values; # dependent variables index in python starts from 0 #splitting the dataset into the traiing set and test set from sklearn.cross_validation import train_test_split columns_train, columns_test, label_train, label_test=train_test_split(columns,label, test_size=0.2, random_state=0) #if 10 observations/sample then 0.2 means two observations in a test set and 8 observations in test set |
Posted in Machine Learning
Machine Learning Mastery
Posted in Machine Learning
Machine Learning in MATLAB: KNN
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dataset=csvread('F:\Machine Learning Training\OneDrive-2017-10-28\Datasets\clusterincluster.csv',1,0); label = dataset(:,3); dataset = dataset(:, 1:2); rng(2); Mdl =fitcnb(dataset, label, 'CrossVal', 'on','kfold',10); Mdl =fitcdiscr(dataset, label, 'CrossVal', 'on','kfold',10); yfit=kfoldPredict(Mdl); conf=confusionmat(label,yfit); gscatter(meas(:1),meas(:,2),species,'') |
Statistics: For Machine Learning: Random Variables : Discrete and Continuous
https://www.youtube.com/watch?v=rifK8BtHaYI
Must See:
Posted in Machine Learning, Research, Statistics
Tagged Machine Learning, Statistics
Training Set, Validation Set, Test Set
Training Set is a subset of the dataset used to build predictive models.
Validation Set is a subset of the dataset used to assess the performance of model built in the training phase
– It provides a test platform for fine-tuning model’s parameters and selecting the best performing model
– Not all modeling algorithms need a validation set
Test set or unseen examples is a subset of the dataset to assess the likely future performance of a model.
– If a model fits the training set much better than it fits the test set. Overfitting is probably the cause
Binary Classification(two class classification)
true|false, 1|0, -1|+1, male|female
Multi-class classification problems can be seen as binary classification problems.
Model Evaluation:
Machine Learning in Easy Way
Deep Learning, Deep Neural Network:
Posted in Data Science, Machine Learning
WEKA
@relation weather
@attribute outlook {sunny, overcast, rainy}
@attribute temperature numeirc
@attribute humidity numeric
@attribute windy {TRUE,FALSE}
@attribute play {yes,no}
@data
sunny, 90, 77, TRUE, no
overcast, 88, 90, FALSE, no
Difference between AI, Machine Learning, NLP and Deep Learning
Different terms for:
Difference between AI, Machine Learning, NLP and Deep Learning
Different terms for:
