#PPT Orientation notebook

[amberluvsbugs]

I must know the pages your art is in within the orientation notebook

Oh good point, I never did show off the stuff I did for the Orientation book did I? Here are all the art pieces I did for it :D

I was not in charge of any of the writings that are in the notebook, I was not part of it as I was just an artist for it XD But It's still so wild to see my work and be part of a scholastic book. Big thank you to Nized for sending me a signed copy of the book :D

[cherrytimemachine]

I just realized something about the Red Smoke.

Is the smoke like... the key to immortality?

It might sound ridiculous, but I realized the smoke was the same color as the red poppy flowers Playtime Co. used, which are hunted at being used to create this everlasting life in the experiments.

What if the red smoke is a gas version of the chemicals from the poppy flowers, and they were testing it on the children in Playcare to see if they would achieve that immortality under the gauze of "helping with sleep?"

I think this is specifically Elliot's idea. There's that note in his office about experimenting on rats and how whoever wrote the note is sure that the poppy flower contains the secret to prolonged life. It was Ludwig who created the Poppy doll in the 50s, as well as being attributed as the creator of the Smiling Critters as stated in the orientation notebook (despite P.W. claiming that Jimmy Roth had taken credit for the Smiling Critters before they flopped because he anticipated them being popular).

If anything, I think the Red Smoke could be an advanced version of his trials with the poppy flowers, and since it's his toyline that had the Catnap doll, which was giving children violent nightmares and used as the conduit for the Red Smoke, it seems like Elliot may have been responsible for the smoke.

Perhaps the smoke was one method they used to select children for the experiments. Marie Payne was plagued by a nightmare of a monster because of the smoke, and she went on to be selected as the experiment for Mommy Long Legs. Is the reaction to the smoke somehow connected to what made her a good candidate for the experiment? Like, was it indicative of certain brain functions they were looking for?

Who knows, my thought process is spiraling at the moment.

[phoenixragdollppt]

Transmission: Found - Q&A - Project Phoenix

It was supposed to be a normal day.

One normal day at the Playtime Factory. How wrong were they?

Children missing…. Toys coming to life and pouncing… blood and scream everywhere…

Through the mass hysteria, he ran to one of the offices, locking the door behind him as he glanced at the calendar: August 8, 1995.

And then Romero woke up from his trance. He glanced down at the bouquet he held in his hands, dropping them immediately. Was this a vision of what was to come or did it already happen? Either way, he knew one thing: he had to stop the Hour of Joy from happening. But how?

… The Phoenix will rise from the ashes and fields of Poppies…

Dr. Romero Belrose is Available for Questions!

[fridaysmind]

Shifting priorities

The Doctor x reader (platonic)

Okay, I've only written on Transformers, but seeing the new installment of PPT just made me smile and sit down to write. I love the scientist characters too much. Warning: mention of organs and violent experiments, possible spoilers. If you want me to write you something, feel free to request it!

Yes. Yes, he knows no mercy, yes, he's ruthless and cruel. So what? If even half the employees in this company were as logical, goal-oriented, the greatest things were created long ago. If that snot-nosed jerk Ludwig, with his inspirational speeches and penetratingly understanding gaze, would stop acting like a softy, immortality would not be a dream, but a matter of money. Sure, these assholes would be sure to talk about the good for the world, but who gives a damn? They don't understand anything at all, make heroes out of themselves, sympathize, pity, as if they are not the ones watching bloody experiments on cameras, as if they are not the ones keeping living corpses in cages without food

Let any of them call Sawyer an asshole, so be it, but he was honest enough, at least with himself. He knew who he was and didn't try to appear different.

Some of the employees laughed at him when he brought you, a kid, into his cleanest (and relatively) office for notes and paperwork. They threw jokes about his demotion to babysitter or his willingness to leave his job and go into fatherhood. The doctor had no trouble putting them in their place.

They don't understand because of their own feeble-mindedness, Sawyer says to himself, looking down into your big, overly intelligent eyes. He took this kid away, like finding a diamond in a pile of dirt, sand, and debris. He knew those test results, he knew that communication style. It was hard not to recognize himself in your face. A kind of little genius who'd been so lucky to get into the orphanage.

You're definitely different from the other kids, you don't look at him like he's the last hope, like you're a yard dog, you don't act like a nasty snotty brat, none of that. But he sees respect, he sees that one genius recognizes and acknowledges another and it rubs off on his ego. You laboriously write something out of his study guides by the light of a desk lamp, read his notes, speak of him to others with reverence, causing him something resembling a surge of pride.

Kids are always too curious, especially the smart ones, and you were out of the question. Of course you did sneak in during one of his experiments. He can blame himself for not locking the door. He could, yes, but he won't. Another body opened up before him like a flower bud, not moving as he carefully separated the marrow with a scalpel and as your stupid face crawled out from the other side of the bunk, making him shriek in fright.

He was almost on the verge of a breakdown, it had all started out so well, now he'd have to either keep you on a leash or get rid of you altogether, the kids can't live with themselves after a sight like that!

But oh, oh, he remembered why he chose you. Staring emotionlessly at the pale face of the girl you had definitely previously known, you point a finger towards her head asking to see the actual brain. He calms down in an instant, noting to himself again what a genius he is for discerning the right specimen.

As the doctor continues to poke around inside the children, you sketch out cerebral gyrus in your notebook, interjecting now and then about the purpose and name of certain parts of the large hemispheres of the brain. Wonderful child…

As the years of his work go by, you grow up. You enjoy interacting with experiment 1166, stroking his colorful fur, throwing him things to bring back. You're aware of his human nature, as well as many other things, but you remain as he chose you to be–cold and indifferent.

The Doctor notes some signs of savagery in you, very slight, but that's not surprising when a child grows up underground, in the company of adults, experiments, and beast-like unintelligent creatures. You can survive it.

***

His first reaction when he wakes up, immobilized, split into pieces and placed in the damn machine–worrying about himself. Not that it's unexpected. He remembers you pretty quickly, too. Where are you, where is his favorite apprentice? He asks questions, demands answers, threatens, but a short 'run away' is all he gets in response.

Immersed in darkness and silence, abandoned by traitors who only turn when they need his brainpower, he thinks of you. You're still not as bright as he is, but your company was much more pleasant than this one. Did you just run away, leaving him alone? You don't think of him even after all these years together? You grew up around him, he taught you so many things that he knew himself, didn't you get attached?

What a silly thing to say, he doesn't get attached, and you're so much like him that you're hardly different in this. Sawyer can't help but feel something unpleasant at the thought. Abandoned, all traitors and all abandoned him!

***

The ray of light in this prison was your sudden voice. He thought he had lost his mind, he mean even more, but no, you were definitely here, the cameras didn't lie. He couldn't help but scare you a couple times, just for fun, understand the old man, he was so bored here! But he helps you get to him, genuinely happy to be able to socialize again. No, he hasn't become like those soft-spoken idiots in the factory, it's just nice to talk to a decent person, that's all.

You stay by his side survived by nothing short of a miracle when the Prototype himself visits the Doctor after the Hour of Joy. They need his mind, they need his intelligence and knowledge. All that, but not you.

Sawyer almost squeals, screaming that he will not help them under any circumstances if they touch such a marvelous specimen, he is uncompromising, unafraid of the threats of a huge creature that makes even your mouth dry up with a semblance of worry.

You're staying, alive again by a miracle. and under strict surveillance by everyone. No one here trusts you, nor will they. You don't expect them to be kind, though.

The Prototype has warned Sawyer that your feeding is only the Doctor's own responsibility and goes into the shadows. You are left alone with each other, simultaneously tongue clucking and hissing the same curse. Everyone here is such an asshole.

[analyticsindiam]

ZS Hiring Hackathon : Patient Drug-switch Prediction

Machine Learning and Data Science have stolen the attention of the young generation who are seeking an exciting and well-paid career. With the advent of growth in data volume and technology the gap between Machine Learning Engineers and Data Scientist is narrowing leading companies to look for full-stack data scientists. The demand for such folks with Machine learning and Data Science skills is exponentially increasing and organizations are struggling to find their best fit. Good MLDS profile not only requires a strong analytical and engineering background but also needs a good understanding of the algorithms, advanced statistics, optimization approaches, coding & distributed computing skills. One of the few possible ways to master this new domain is through constant learning, practice and showcasing of skills through hackathons. This is where MachineHack is going to help. With the help of our top hackathons, you can become an expert in handling data and build a path to a successful Machine Learning and Data Science career. MachineHack and ZS Associates bring to you the “Patient Drug-switch Prediction Hackathon” Problem Description Armanik, a multinational pharmaceutical company based in Texas, USA, is one of the largest pharmaceutical companies by both market capitalization and sales. Armanik manufactures drugs across multiple therapy areas – Cardiovascular, Diabetes, HIV and Immunology therapy. Their innovative SGLT 2 is the market leader in diabetes therapy. Recently, the company announced that they have successfully completed a Phase 3 trial for an Anti-TNF drug in Rheumatoid Arthritis therapeutic. The company expects to get approval for its new drug in the next 6 months. Given the competition in the market, Prakash Vishwanathan, CEO of Armanik, has reached out to ZS to help identify the patient population in the U.S who are likely to switch any product in the RA market. ZS has proposed a machine learning-based approach using medical transactional data to first identify the factors that are most closely associated with the switching RA patients that will help predict patients who are likely to switch in the near term.  Can you help ZS in achieving the below-mentioned objectives?

Data Sets  File Descriptions : Train_data.csv – Data for training (This is a transactional data for feature creation)Train_labels.csv – Outcome flag for train patients (1/0)Test_data.csv – Data for testing (Create final features for modelling)Fitness_values.csv – Fitness values for features created with train data. Must be used to match the fitness values with the Feature created using Train Data Only.Sample Submission.csv – Sample submission Format to submit the Predictions (Don’t Shuffle the Patient_ID, Keep the sequence entact). Train_data.csv

Data Size: Train Data: 627 MBTest Data: 273 MB Packages allowed: PandasNumpyScipyNumbaCython extensionoperator Click here to participate. ABOUT ZS ZS is a professional services firm that works side by side with companies to help develop and deliver products that drive customer value and company results. We leverage our deep industry expertise, leading-edge analytics, technology and strategy to create solutions that work in the real world. With more than 35 years of experience and 6,000-plus ZS-ers in 23 offices worldwide, we are passionately committed to helping companies and their customers thrive. Our most valuable asset is our people—a fact that’s reflected in our values-driven organization in which new perspectives are integral and new ideas are celebrated. We apply our knowledge, capabilities and innovation-oriented approach in industries ranging from healthcare and life sciences to high-tech, financial services, travel and transportation, and beyond. Rules Eligibility: Hackathons are open to all registered users at www.machinehack.com, a participant must be 18 years or older.Only one account is allowed per participant; submissions from multiple accounts will lead to disqualification. This is an individual exercise.We expect that you respect the spirit of the competition and do not cheat. Privately sharing code or data is not permitted—any case of code plagiarism will result in the disqualification of all users involved.It is obligatory to submit a well-commented and reproducible source code that you would generate as part of this contest in .zip or .tar compressed archive or the submission will not be considered.The ideal candidate is expected to hold 2-6 years of experience in working as a Data Scientist or a Machine Learning EngineerThe leaderboard will be updated on the basis of the AUC score of the submitted predictions.Users must have an updated MachineHack profile and must specify their LinkedIn for final shortlisting.  Submission limits : You can make a maximum of 3 excel file submissions in a day. Timeline Hackathon will be live from 3rd January 2020 to 13th January 2020. Phase 1:  AUC evaluation of submitted predictions - 3rd January 2020 to 10th January 2020. Phase 2:  Time complexity evaluation of Submitted code files - 11th January 2020 to 13th January 2020. Submitting Your Files For Evaluation

Phase 1 Submission window: January 3rd to January 10th 2020 The hackathon assignment requires participants to submit an excel file (Only .xlsx files are allowed) containing the unique identifier  ‘patient_id’ and the corresponding prediction classes ‘outcome_flag’. The submissions are evaluated on AUC score and the leaderboard is updated. Phase 2 Submission window: January 11th to January 13th 2020 The phase 2 submission window (FINAL SUBMISSION) will be enabled to share the following files as a zip  post 10th January : The phase 1 submission file with the best AUC score on the leaderboard. (Best Score.xlsx)A csv file containing a list of all the features along with their fitness value. (Fitness_Score.csv)A python script file that can be executed on a machine with RAM of 16 GB to recreate the features and fitness values. (Feature_Pipeline.py)A well commented and reproducible source code(python script) for the best AUC which will be evaluated for time complexity. (Model.py)Fully documented approach in a PPT. Note: Participants must upload the above files in a zip archive to a submission portal which will be enabled on January 11th 2020. Bounty

The best submission will receive a Macbook and a free pass to Machine Learning Developers Summit 2020.The shortlisted participants will get an opportunity to present their approach at MLDS 2020 to a panel of experienced leadership of ZS-ers and participants of the summit.  The top 15 participants will get an opportunity to be interviewed for the role of Data Scientist/ Machine Learning Engineer at ZS Associates (The role can be chosen based on your expertise area between the two roles) Click here to participate. Evaluations THE CANDIDATES WILL HAVE TO MAKE SUBMISSIONS AS PER THE GUIDELINES MENTIONED BELOW: Objective 1: Auto Feature Engineering A CSV file containing a list of all the features along with their fitness value.

Once the set of mandatory features is created using the training data, evaluate the fitness of these features using the following methodology. (A starter python notebook is available here) Any submission with >1% of error – sum of % errors across fitness values of all features (~40000 features), will be considered as Invalid. Objective 2: Patient Switching Probabilities Test Set Predictions: The test set predictions are evaluated using AUC. An excel file (.xlsx only) containing the prediction probability for all the patients in the test data. The top submissions will be decided based on the leaderboard score and evaluation of other submission documents (code file, .csv file, supporting notebooks, model pipeline- .py file or .ipynb format). All the good submissions will be eligible to receive the bounties Participate Read the full article

[taracotarao]

Intel i7-6660U搭載、14.1インチのハイスペックノートパソコンALLDOCUBE i7Book の実機レビューです。

14.1インチながらに1.364kgと薄型軽量でバッテリーも約8時間もってくれてモバイル性抜群。フルサイズのキーボードを搭載しており、デザイン・性能ともに文句なしで、重たいページもサクサク読み込みビジネス用途にもガンガン使える頼れるPCです。

現在Banggoodではクーポン特別セール中で99台限定で70%割引の$479.99！こんなに安くて良いの？ってぐらいコスパ抜群です！セールは8月17日より1週間。今日入れて残り2日となりますので欲しい人は急いでくださいね。

セールリンク：ALLDOCUBE i7Book 14.1 inch Intel i7-6660U 8GB RAM 256GB SSD 51.3Wh Battery Full-Featured Type-C 90% Narrow Bezel Notebook

ALLDOCUBE i7Book ���ビュー

ALLDOCUBE i7Bookの外観写真

今回はBanggoodさんからサンプル提供して頂いたのですが、パソコンだから運送会社も丁寧に運んでくれたようで、外箱もこのような状態でとってもきれいな状態で届きました。

段ボールから取り出したところですが、例え少々衝撃を受けても安心という程に厳重梱包でした。

パッケージ内容はALLDOCUBE i7Book本体、電源アダプター（日本仕様ではないコンセントプラグ）、日本語対応のマニュアルでした。

日本仕様ではないとはいえ、57W（19V 3A）の電源アダプターは100V対応なので、変換プラグを使えばそのまま日本でも利用できます。

左の白い変換プラグのようなものが必要となりますが、変換プラグを通す事で、付属の電源アダプターの利用が可能です。

またALLDOCUBE i7BookはTYPE-CポートでのPD高速充電にも対応しているので、PD充電対応のモバイルバッテリーなども利用可能です。57Wの出力が可能なPD対応充電器であればスマホ用のでも利用可能なので、TYPE-Cポートから電源を取ることで変換アダプターを別途準備する必要はありません。

ALLDOCUBE i7Book自体の重さは1.364kgと14.1インチにしては軽めです。フレームはアルミニウム製で、サンドブラスト処理が施された蓋部分にシンプルなロゴ1つのみで、好き嫌いの無さそうなデザインです。

本体サイズは32.20 x 21.20 x 1.59 cmとなっており、とても薄型なのでバックに入れて持ち歩くのも苦になりません。

前後どちらから見ても薄型。エッジの加工も程よい角度を残しつつも丸みを帯びたデザインで、手触りも良いです。

拡張ポートは豊富で、右サイドにはMicro SDスロットと、USB 3.0ポートを2つと、3.5mmイヤホンジャックを搭載しています。

本体左サイドにはDC電源ジャック、充電もできるTYPE-Cポート、HDMIポート、USB 3.0ポートとなっています。

背面には大きなファンの穴が開いており、Intel i7-6660UのCPUのパフォーマンスを最大に活かせる排熱が行えます。しかし、ファンが回る際に少し甲高いキーンという機械音が鳴るので、神経質な方はそこが少し気になるかもしれません。

YOUTUBEの1080p再生程度ではファンが最大にまわる事はないのですが、4K動画の再生やWindowsのアップデートやベンチマークテストというような高負荷をかけた場合はファンが最大に回ってしまいます。高負荷な作業をする場合は少し場所を選びそうです。

とは言え、VAIOも最高にファンが回った場合はそこそこ騒音がするので、それより少しだけ騒がしいかなというレベルで、特に異音がするという事はありません。

底部には滑り止めのゴムが付いているのですが、少し高さがあり排熱効果も高まりそうです。

液晶パネルの上には1.0MPのカメラがついており、静止画は0.9MP 16:9 1280×720、0.3MP 4:3 640×480、0.08MP 4:3 320×240の解像度が選べます。動画は720p 16:9 30fps、480p 4:3 30fps、240p 4:3 30fpsが選べます。

画質はビデオチャットが行えない事はないという程度で、夜間の蛍光灯の下では少し白っぽく写ってしまいあまり鮮明ではありません。

フルサイズのキーボードを搭載しています。右端1列によく海外モデルであるキー配列がありますが、14.1インチというボディーを充分に使っており、キーが小さくなることなどなく、とてもタイプしやすいです。

右上にあるボタンはただの電源ボタンで、指紋センサーなどは搭載していません。

キーボードはアイソレーションタイプで、キーピッチも充分にとってあり、ネイルをしている私でも爪が引っかかるような事などありません。ネイルをしている人などはこのタイプのキーボードはとても使いやすいです。

また適度なキーストロークでしっかりした打鍵感もありつつあまり力を入れずに入力できるので、長時間のタイプをしても疲れません。タイプオンもとても静かで、タイプ中にキーボードがたわむという事もなく、ボディーはとてもしっかりした作りです。

バックライト無しで、キートップはシールっぽい刻印になっているのが少��残念なポイント。でも現在Banggoodでは、日本語配列のステッカーを無料でプレゼントするキャンペーンを行っています。

こちらのようなステッカーをプレゼントしてもらえるので、海外のパソコンの英語配列が嫌いという方でも、これならハードルが下がるのではないでしょうか。

タッチパッドは大き目なサイズ感で、タッチの反応も正確でとても使いやすいです。Microsoft Precision TouchPadに対応しており、10ポイントマルチタッチジェスチャーが利用できるので、マウス無しの環境でも快適に操作する事ができます。

日本語対応のWindows10搭載ですぐに使える

ALLDOCUBEブランドは中国のメーカーになりますが、搭載のWindowsは日本語にも対応があるWindows 10になります。Xiaomi Airなど、Windows Chinaがインストールされている機種の場合は、わざわざ日本語化をする為にwindowsのクリーンインストールなどの少し複雑な作業が必要となりますが、ALLDOCUBE i7Bookは特に難しい設定などなくすぐに利用できます。

起動したらまず上記のような画面の英語で起動し、日本語を選択するだけで写真のように日本語表示となり、その後の設定はコルタナの指示通りに進むだけで大丈夫ですので、PCにあまり明るくない人でも簡単に設定を行��事ができます。

IPSのノングレア液晶で見やすい

ALLDOCUBE i7Bookは1920×1080（FHD）のIPSスクリーンを搭載しています。ピクセル密度は157PPIです。非光沢画面なので、光沢画面に比べて少しくすんで見えるのですが、目の疲れにつながってしまう反射は皆無です。また視野角は178度とどこから見てもとてもキレイな液晶で、オフィス作業などはとても快適です。

同じく14インチのVAIO S14との比較です。両者画面の明るさは最大にしています。ALLDOCUBE i7Bookは左、上、右の3サイドのベゼルがとても薄くなっており、デザイン自慢の最新のVAIOにも引けを取らないデザインです。両者ノングレア液晶です。

蓋の開閉は135°程度は開きます。よく見たらスクショの写真は139°になっちゃってますが、開閉は135°です。非光沢画面なので、これだけ倒れれば見やすい角度は充分に調節できるのではないかと思います。

またGoogle ChromeでのYOUTUBEの4K動画の再生も可能です。スピーカーは説明書にはシングルと記載がありましたが、キーボードの両サイドにステレオスピーカーが搭載されています。音質はノートパソコンの中では上位にランクインする音質で、厚みのある低音にクリアな中高音で、動画の再生などが楽しくなりそうです。音量をあげても音割れ等なくいい音です。

また、私のサイトのBanggoodクーポンの情報量多すぎの重たいページを20個開いても固まる事などはなかったです。重たいページを開くのもビュンビュンで、とっても快適でした。

バッテリーは8時間以上の動画再生に耐えうる性能

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再生スタート

約3時間半後

約6時間後

約7時間後

写真は1度目のテストで、終了したと思っていたWindowsの更新がまだ完全には終了しておらず、バクグラでダウンロードされていたので少しだけ動画の連続再生時間が短くなってしまっていますが、18：19よりテストスタートして25：08までの約7時間再生後も12%の残量で、残り40分となっていました。

スタート当初残り3時間45分となっていたので、バッテリー少ないって思ったのですが、設定いじってないのにそこから約3時間半たってもほぼ同じ残り3時間半程度となっていました。この意味が良く分からないのですが、バッテリー性能は優秀だと思います。

説明書には通常の明るさと音量だと、動画再生は9時間可能と記載があります。温度などの環境で多少の誤差はあると思いますが、2回目のテストでは8時間ちょいはいけました。

CPU性能・ベンチマーク

ALLDOCUBE i7Bookには、Intel Core i7-6660Uで最大3.4GHzのターボと2.4GHzでクロックされるデュアルコアCPUが搭載されています。これはひと昔前（2016年リリース）のCPUにはなってしまいますが、Core i7というだけあって通常使用では充分に快適な性能を発揮します。

ストレージは256GBのSSD（SATA)、メモリは8GBとなります。欲を言えば、メモリは16GB欲しいところですが、これは約5万円という価格帯では妥協ポイントになるかと思います。

それでもALLDOCUBE i7Bookで出来る事は多く、動画の編集や高解像度の写真の編集も快適に行えます。ブログの編集や、オフィス作業、簡単なゲームなども不便なく行えます。

●Geekbench 5 Score

Geekbench 5 Scoreでは、Single9Core 929, Multi-Core 2022。

●Cinebench R20

Cinebench R20 CPUベンチマークスコアは743。

●WEI Viewer

Vaio S15 bench

ALLDOCUBE i7Book

上がVaio S15 Core i7-7700HQ Intel Graphics 630で、下がALLDOCUBE i7Book Intel Core i7-6660U Intel Graphics 540になります。

Vaioの圧勝だろうと思っていたところ、GPU性能はALLDOCUBE i7Bookの方が良くて少し驚いています。もしかしてバクグラでこのブログを書いていたりしたので、それが原因かもしれませんが・・

●CrystalDiskMark

ベンチマーク計測する度に計測値が変わるので、2枚載せておきますね。

CrystalDiskMarkテストでは、読み取りテストでは553 MB/秒（MB /秒）、書き込みテストでは436 MB/秒でした。NVME標準SSDと比較すると見劣りしますが、ブログを書いたりネットサーフィンなどを行う場合は、読み書きが遅いなと思う事などはなくとても快適です。

●ドラクエ

ドラクエでは、最高品質とFHD解像度にしても快適となる性能です。

●ファイナルファンタジー

ファイナルファンタジーのようなリッチな描写のゲームは動作困難というレベルの738というスコアでした。

ALLDOCUBE i7BookはゲーミングPCではないのでゲーム性能抜群とはなりませんが、ドラクエレベルの簡単なゲームは普通に快適に遊べます。 [template id=”77842″]

ALLDOCUBE i7Book スペック詳細

主な特徴 ブランド：ALLDOCUBE モデル名：i7Book カラー：シルバー 素材：アルミニウム合金, CNCテクノロジー OS：Windows 10 CPU：Intel Core i7-6660U CPU周波数：Quad-Core,2.4GHz-3.4GHz プロセス技術：14nm 消費電力：15W GPU：Intel Graphics 540 キャッシュストレージ メモリ：8GB LPDDR4 ストレージ：256GB SSD ネットワーク WI-FI：IEEE 802.11a/b/g/n/ac 2.4GHz/5.0GHzデュアルバンド Bluetooth：4.2 ディスプレイ 画面サイズ：14.1インチ 表示比率：16：9、90％の比率 画面の解像度：1920 x 1080（FHD） スクリーンタイプ：IPSマット カメラ フロント1.0MP 接続性 USB3.0 ×3 DC電源ジャック TYPE-Cポート HDMIポート Micro SDスロット 3.5mmイヤホンジャック メディアフォーマット 画像フォーマット：JPG、BMP、PNG オーディオフォーマット：MP3、WMA、WAV、OGG、FLAC、APE ビデオフォーマット：MEPG1 / 2/4、H.263 / H.264 / H.265、RMVB、WMV / VC-1、MVC、AVS、MPEG。（最大4K） MS Office形式：Word、Excel、PPT 言語：日本語対応 バッテリー 4500mAh / 11.4vリチウムイオンポリマーバッテリー サイズ 32.20 x 21.20 x 1.59cm, 1.36kg

ALLDOCUBE i7Book の特別セール情報

現在Banggoodでは通常価格$549.99のところ、$479.99になる特別クーポンセール開催中。なんと明日24日に終わってしまいますので、欲しい人は大至急決断してくださいね！ｗ

セールリンク：ALLDOCUBE i7Book 14.1 inch Intel i7-6660U 8GB RAM 256GB SSD 51.3Wh Battery Full-Featured Type-C 90% Narrow Bezel Notebook

セールページには以下のボタンが表示されています。まだ現在$479.99で購入できるボタンがクリックできます。クリックするとクーポンが表示されるので、それをカート内で入力して割引を適用させてくださいね。

ALLDOCUBE i7Book クーポン情報

ALLDOCUBE i7Book クーポン & セール情報の記事では、割引クーポンが追加になり次第記載しています。

クーポンはCOPYをクリックでコピーできます。

商品名 クーポン セール価格 台数 有効期限 ALLDOCUBE i7 Book 14.1 inch 8GB Ram 256GB SSD Windows10 Laptops Intel Core i7-6660U Processor Notebook – White China Intel I7 フラッシュセール $560.49 50 9月1日 ALLDOCUBE i7Book 14.1 inch Intel i7-6660U 8GB RAM 256GB SSD 51.3Wh Battery Full-Featured Type-C 90% Narrow Bezel Notebook BGJPABi7Copy $529.99 10 8月20日 ALLDOCUBE i7Book 14.1 inch Intel i7-6660U 8GB RAM 256GB SSD 51.3Wh Battery Full-Featured Type-C 90% Narrow Bezel Notebook プロモ価格 $549.99 50 8月17日

　

ALLDOCUBE i7Book レビュー Intel i7-6660U搭載14.1インチ、重さ1.36kg薄型軽量でビジネス用途にもいけてモバイル性抜群、コスパ最強！ 明日迄特別セールで$479.99です！ Intel i7-6660U搭載、14.1インチのハイスペックノートパソコンALLDOCUBE i7Book の実機レビューです。 14.1インチながらに1.364kgと薄型軽量でバッテリーも約8時間もってくれてモバイル性抜群。フルサイズのキーボードを搭載しており、デザイン・性能ともに文句なしで、重たいページもサクサク読み込みビジネス用途にもガンガン使える頼れるPCです。 現在Banggoodではクーポン特別セール中で99台限定で70%割引の$479.99！こんなに安くて良いの？ってぐらいコスパ抜群です！セールは8月17日より1週間。今日入れて残り2日となりますので欲しい人は急いでくださいね。 セールリンク：ALLDOCUBE i7Book 14.1 inch Intel i7-6660U 8GB RAM 256GB SSD 51.3Wh Battery Full-Featured Type-C 90% Narrow Bezel Notebook…

[analyticsindiam]

ZS Hiring Hackathon : Patient Drug-switch Prediction

Machine Learning and Data Science have stolen the attention of the young generation who are seeking an exciting and well-paid career. With the advent of growth in data volume and technology the gap between Machine Learning Engineers and Data Scientist is narrowing leading companies to look for full-stack data scientists. The demand for such folks with Machine learning and Data Science skills is exponentially increasing and organizations are struggling to find their best fit. Good MLDS profile not only requires a strong analytical and engineering background but also needs a good understanding of the algorithms, advanced statistics, optimization approaches, coding & distributed computing skills. One of the few possible ways to master this new domain is through constant learning, practice and showcasing of skills through hackathons. This is where MachineHack is going to help. With the help of our top hackathons, you can become an expert in handling data and build a path to a successful Machine Learning and Data Science career. MachineHack and ZS Associates bring to you the “Patient Drug-switch Prediction Hackathon” Problem Description Armanik, a multinational pharmaceutical company based in Texas, USA, is one of the largest pharmaceutical companies by both market capitalization and sales. Armanik manufactures drugs across multiple therapy areas – Cardiovascular, Diabetes, HIV and Immunology therapy. Their innovative SGLT 2 is the market leader in diabetes therapy. Recently, the company announced that they have successfully completed a Phase 3 trial for an Anti-TNF drug in Rheumatoid Arthritis therapeutic. The company expects to get approval for its new drug in the next 6 months. Given the competition in the market, Prakash Vishwanathan, CEO of Armanik, has reached out to ZS to help identify the patient population in the U.S who are likely to switch any product in the RA market. ZS has proposed a machine learning-based approach using medical transactional data to first identify the factors that are most closely associated with the switching RA patients that will help predict patients who are likely to switch in the near term.  Can you help ZS in achieving the below-mentioned objectives?

Data Sets  File Descriptions : Train_data.csv – Data for training (This is a transactional data for feature creation)Train_labels.csv – Outcome flag for train patients (1/0)Test_data.csv – Data for testing (Create final features for modelling)Fitness_values.csv – Fitness values for features created with train data. Must be used to match the fitness values with the Feature created using Train Data Only.Sample Submission.csv – Sample submission Format to submit the Predictions (Don’t Shuffle the Patient_ID, Keep the sequence entact). Train_data.csv

Data Size: Train Data: 627 MBTest Data: 273 MB Packages allowed: PandasNumpyScipyNumbaCython extensionoperator Click here to participate. ABOUT ZS ZS is a professional services firm that works side by side with companies to help develop and deliver products that drive customer value and company results. We leverage our deep industry expertise, leading-edge analytics, technology and strategy to create solutions that work in the real world. With more than 35 years of experience and 6,000-plus ZS-ers in 23 offices worldwide, we are passionately committed to helping companies and their customers thrive. Our most valuable asset is our people—a fact that’s reflected in our values-driven organization in which new perspectives are integral and new ideas are celebrated. We apply our knowledge, capabilities and innovation-oriented approach in industries ranging from healthcare and life sciences to high-tech, financial services, travel and transportation, and beyond. Rules Eligibility: Hackathons are open to all registered users at www.machinehack.com, a participant must be 18 years or older.Only one account is allowed per participant; submissions from multiple accounts will lead to disqualification. This is an individual exercise.We expect that you respect the spirit of the competition and do not cheat. Privately sharing code or data is not permitted—any case of code plagiarism will result in the disqualification of all users involved.It is obligatory to submit a well-commented and reproducible source code that you would generate as part of this contest in .zip or .tar compressed archive or the submission will not be considered.The ideal candidate is expected to hold 2-6 years of experience in working as a Data Scientist or a Machine Learning EngineerThe leaderboard will be updated on the basis of the AUC score of the submitted predictions.Users must have an updated MachineHack profile and must specify their LinkedIn for final shortlisting.  Submission limits : You can make a maximum of 3 excel file submissions in a day. Timeline Hackathon will be live from 3rd January 2020 to 13th January 2020. Phase 1:  AUC evaluation of submitted predictions - 3rd January 2020 to 10th January 2020. Phase 2:  Time complexity evaluation of Submitted code files - 11th January 2020 to 13th January 2020. Submitting Your Files For Evaluation

Phase 1 Submission window: January 3rd to January 10th 2020 The hackathon assignment requires participants to submit an excel file (Only .xlsx files are allowed) containing the unique identifier  ‘patient_id’ and the corresponding prediction classes ‘outcome_flag’. The submissions are evaluated on AUC score and the leaderboard is updated. Phase 2 Submission window: January 11th to January 13th 2020 The phase 2 submission window (FINAL SUBMISSION) will be enabled to share the following files as a zip  post 10th January : The phase 1 submission file with the best AUC score on the leaderboard. (Best Score.xlsx)A csv file containing a list of all the features along with their fitness value. (Fitness_Score.csv)A python script file that can be executed on a machine with RAM of 16 GB to recreate the features and fitness values. (Feature_Pipeline.py)A well commented and reproducible source code(python script) for the best AUC which will be evaluated for time complexity. (Model.py)Fully documented approach in a PPT. Note: Participants must upload the above files in a zip archive to a submission portal which will be enabled on January 11th 2020. Bounty

The best submission will receive a Macbook and a free pass to Machine Learning Developers Summit 2020.The shortlisted participants will get an opportunity to present their approach at MLDS 2020 to a panel of experienced leadership of ZS-ers and participants of the summit.  The top 15 participants will get an opportunity to be interviewed for the role of Data Scientist/ Machine Learning Engineer at ZS Associates (The role can be chosen based on your expertise area between the two roles) Click here to participate. Evaluations THE CANDIDATES WILL HAVE TO MAKE SUBMISSIONS AS PER THE GUIDELINES MENTIONED BELOW: Objective 1: Auto Feature Engineering A CSV file containing a list of all the features along with their fitness value.

Once the set of mandatory features is created using the training data, evaluate the fitness of these features using the following methodology. (A starter python notebook is available here) Any submission with >1% of error – sum of % errors across fitness values of all features (~40000 features), will be considered as Invalid. Objective 2: Patient Switching Probabilities Test Set Predictions: The test set predictions are evaluated using AUC. An excel file (.xlsx only) containing the prediction probability for all the patients in the test data. The top submissions will be decided based on the leaderboard score and evaluation of other submission documents (code file, .csv file, supporting notebooks, model pipeline- .py file or .ipynb format). All the good submissions will be eligible to receive the bounties Participate Read the full article