Achmad Solichin

Rekomendasi 5 Kursus Online Machine Learning untuk Pemula | Gratis Bersertifikat. Sebuah utas mini

Indonesian Traditional Batik *made with Gemini Nano Banana

Convolutional Neural Network (CNN), illustrated by @GeminiApp Prompt 👇

@JafarNajafov AI

Everyone is hyped about Google Gemini Pro… but barely anyone knows how to actually use it to replace real work. I collected 300+ mega prompts that turn Gemini into a full-blown productivity engine. Comment "AI" and I’ll DM you everything.

I just finished the Quizizz AI Certification and learned how to create, adapt, and differentiate my content in seconds! quizizz.com/home/quizizz-a… via @quizizz

@jusnanasap Boleh tau kesulitannya apa?

@achmatim pak saya sedang kesusahan membangun game menggunakan gdevelop, apa bapak bisa membantu inggih? terima kasih🙏

Segera tayang di Kanal Youtube, bagian akhir dari tutorial bikin game dg GDevelop. Insya Alloh tayang hari Senin, 28 September 2020 jam 8 pagi. instagram.com/p/CFpIMkXH9Mo/…

@gunsnrosesgirl3 In Indonesia, especially in my village, it's called "Kemplung".

Can you say what this is ? twitter.com/tradingMaxiSL/…

@heyrobinai Disclaimer: Not yet available for all countries

2. Mobile Version Google Gemini App is now downloadable from Google Play and the App Store → Android Link: bit.ly/getgemini1 → Google App on iOS: apps.apple.com/us/app/google/…

I think ChatGPT is over. Google has launched Gemini, and it's insane Here are 8 powerful things you can do with Gemini:👇

Hiks hiks. Achmatim.Net

SQLFlow - lumayan membantu memvisualisasikan query, jadi lebih kebayang alurnya terutama jika join banyak tabel. sqlflow.gudusoft.com

“Membekali Gen Y dan Z dengan explore Digital Platform” Hari & Tanggal : Jumat, 22 September 2023 Pukul 15.00 Bersama Dekan Fikom Universitas Prof. Dr. Moestopo, Muhammad Saifulloh @m_saifullah_maksum Dosen Fakultas Teknologi Informasi Universitas Budi Luhur, Achmad Solichin @achmatim Content Creator dan Pelaku UMKM @pacitanku, Sulthon Ahalahudin. Live! di Radio Elshinta dan Media Sosial Elshinta

Hidup bukan ttg siapa yg terbaik, tapi ttg siapa yg berbuat baik. Maka teruslah menjadi baik. Jika beruntung, kita akan ketemu dg orang baik. Jika tidak, maka akan ditemukan oleh orang baik. -kang @kangmaman72

@humaedi @ivosights Kapan2 cerita ivoinsights di kampus ya me. Oke?

Berawal inisiasi ketemuan di Cuppa Coffe Kalibata Mall Sekitar Tahun 2014, Develop Social Media Analytics yang berlanjut develop sistem omni channel untuk call center yang Alhamdulilah masih tumbuh dan berkembang sampai sekarang. @ivosights

@freest_man Video explanation in Indonesian youtu.be/OSxEi1qRlB0 #MachineLearning

🤔 Confusion Matrix - How good was the prediction? 🤔 This topic is repeatedly asked in many Data Science interviews A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known.  It allows the visualization of the performance of an algorithm The confusion matrix is also known as an error matrix.  Each row of the matrix represents the instances in a predicted class while each column represents the instances in an actual class (or vice versa) The name stems from the fact that it makes it easy to see if the system is confusing two classes (i.e., commonly mislabeling one as another) The four values that can be derived from a confusion matrix are True Positives (TP), False Positives (FP), True Negatives (TN), and False Negatives (FN) True Positive (TP) represents the number of correct predictions for the positive class. False Positive (FP) represents the number of incorrect predictions for the positive class. True Negative (TN) represents the number of correct predictions for the negative class.  False Negative (FN) represents the number of incorrect predictions for the negative class The accuracy of a classification model can be calculated using these four values.  Accuracy = (TP + TN) / (TP + TN + FP + FN) Precision is defined as TP / (TP + FP) and Recall is defined as TP / (TP + FN).  F1 score is defined as 2 * ((Precision * Recall) / (Precision + Recall)) Confusion matrices are used in machine learning to evaluate how well a classification model performs.  They are also used in other fields such as signal processing, finance, and medical diagnosis. --- That's a wrap! If you liked this tweet like/retweet and follow @freest_man Cheers!

Programming is changing. Fast! The attached code example uses Gorilla, an open-source Large Language Model that specializes in writing API calls. Gorilla kicks GPT-4's butt at this task. It's also much better than ChatGPT and Claude. The team claims the model is very reliable and reduces hallucinations. They currently support more than 1,600 API calls, and you can contribute yours. To use the model, you start with a natural language query. Gorilla will produce an API call you can invoke. Look at the attached example. I ask the model to detect any Spanish text in an image and translate it to English. The model produces the code I can use to do that. It's awesome! The productivity of every developer worldwide would go through the roof if we had a reliable model that knew how to use any library or framework. (The thing that excites me the most is the ability for anyone to contribute to the model!) Forget the documentation; just write me some code! I can't help but wonder whether we are working ourselves out of a job. As these models improve and write better code, what'll happen with software developer jobs?

🚀🚀🚀🚀🚀 I published the first version of OpenChat, the open-source tool that allow you to run and create custom ChatGPT-like bots, and embed and share these bots anywhere. Repo: github.com/openchatai/Ope… Website: openchat.so Done with @langchain @pinecone 🥰

Pesaing ChatGPT akhirnya dirilis oleh @Google . Akankah lebih baik?

I have a true gift for LLM Devs and the opensource AI community. Several GPT-4 Generated datasets. Toolformer, Instruct, Roleplay-Instruct, and soon, Code-Instruct datasets, all generated from GPT-4. I hope I can give back more! Check them out here: github.com/teknium1/GPTea…

BREAKING: The Twitter recommendation algorithm is now open sourced. github.com/twitter/the-al…

@azamuddin91 Setuju. Dlm proses belajar, jika dihadapkan pada banyak pilihan bhs pemrograman / tools / framework / dll, saya pegang prinsip: "kenali banyak, pelajari satu saja (dulu)".

Gak tau ini popular opinion atau bukan. Menurut saya kalau masih awal belajar gak usah terlalu care soal nanti performanya gimana, bagusan yg mana. Yg penting bisa dulu sih, pilih yg sekiranya populer itu udah lebih dari cukup.