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Clustering Saham Indonesia

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Saham merupakan satuan nilai atau pembukuan dalam berbagai instrumen finansial yang mengacu pada bagian kepemilikan sebuah perusahaan. Perusahaan yang dapat menjual sahamnya ke publik merupakan saham yang sudah listing di bursa atau sudah melakukan Initial Public Offering (IPO)1. Terdapat sekitar 680 saham per Maret 2020 yang sudah listing di bursa efek Indonesia dan jumlahnya terus bertambah seiring berjalannya waktu. Setiap saham yang melantai dibursa memiliki karakteristik yang berbeda beda…

Time Efficiency and Accuracy Improvement using PCA

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If you are familiar enough with data, sometimes you are faced with too many predictor variables that make the computation so heavy. Let us say, you are challenged to predict employee in your company will resign or not while the variables are the level of satisfaction on work, number of project, average monthly hours, time spend at the company, etc. You are facing so many predictor that took so long for training your model. One way to speed up your training process is by reducing the dimension…

Text Generation with Markov Chains

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Natural Language Processing (NLP) is a branch of artificial intelligence that is steadily growing both in terms of research and market values1. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable2. The are many applications of NLP in various industries, such as:

Interpreting Text Classification Model with LIME

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This article will focus on the implementation of LIME for interpreting text classification, since they are slightly different from common classification problem. We will cover the important points as clearly as possible. More detailed concept of LIME is available at my previous post .

DBSCAN Clustering

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Clustering merupakan salah satu bagian dari unsupervised learning. Clustering memiliki tujuan untuk membagi data ke dalam beberapa kelompok berdasarkan kemiripan antar data. Cluster (kelompok) yang baik adalah cluster yang memiliki kemiripan yang besar antar anggota clusternya dan memiliki perbedaan yang signifikan dengan anggota cluster yang berbeda. Clustering dapat diterapkan dalam berbagai bidang seperti segmentasi pasar, cluster profiling, data spatial dll. Metode clustering sangat…

Optimization and Hyper-Parameter Tuning with Genetic Algorithm

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Optimization is important in many fields, including in data science. In manufacturing, where every decision is critical to the process and the profit of organization, optimization is often employed, from the number of each products produced, how the unit is scheduled for production, get the best or optimal process parameter, and also the routing determination such as the traveling salesman problem. In data science, we are familiar with model tuning, where we tune our model in order to improve…

Introduction to Generative Adversarial Network with Keras

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In 2018 a paint of Edmond de Belamy made by machine learning (GAN) was sold for $432,500 in online auction, Christie’s. This made Chritie’s the first auction house that sell works created by machine learning. On an unbelievable price. What do you think about this ? Will machine learning help us create arts, or will it kill our creativity?

Bioinformatics: Decoding Nature’s Code of Life

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It is inarguable that Data Science gives a tremendous impact on today’s industry. Furthermore, it also accelerates the development of basic science research including Biology. Biology harbors some of the most intriguing ideas we may find today; from finding cures for genetic diseases, to something far as breeding mutants! This article will guide you through the wondrous journey of when Data Science meets Biology and how it can impact our life.

Interpreting Classification Model with LIME

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One of many things to consider when we want to choose a machine learning model is the interpretability: can we analyze what variables or certain values that contribute toward particular class or target? Some models can be easily interpreted, such as the linear or logistic regression model and decision trees, but interpreting more complex model such as random forest and neural network can be challenging. This sometimes drive the data scientist to choose more interpretable model since they need to…

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