James, G., Witten, D., Hastie, T., and Tibshirani, R. Credit Card Balance Data [Data file]. USC; Marshall School of Business; Los Angeles, California. [cited 2020 Aug 1]. Available from: https://faculty.marshall.usc.edu/gareth-james/ISL/Credit.csv
I'm going to look at binary classification (two classes) and linear regression. In particular I'm going to use the Credit Card Balance data set (James et al., 2013) to look at how to interpret the linear model once we encode gender.
Set Up
Imports
First, some importing.
# pythonfromfunctoolsimportpartialfrompathlibimportPathimportmathimportosimportpickle# pypifromdotenvimportload_dotenvfromexpectsimport(be_true,expect)importhvplot.pandasimportpandasimportstatsmodels.apiasstatsmodelsimportstatsmodels.formula.apiasstatsmodels_formula# my stufffromgraeaeimportEmbedHoloviews,CountPercentage
The Environment
This loads the path to files.
load_dotenv(".env")
Plotting
This just sets up some convenience values for plotting.
I passed in the index_col argument because the first column is a index column with no header, so it just looks goofy if you don't. There are several columns but I only want Gender and Balance (the credit card balance).
data=data[["Gender","Balance"]]
Middle
The Data
Now that we have the data we can take a quick look at what's there.
Our two classes are "Female" and "Male" and they are roughly, but not quite, equal in number. Now I'll look at the balance.
plot=data.hvplot.kde(y="Balance",by="Gender",color=Plot.color_cycle).opts(width=Plot.width,height=Plot.height,fontscale=Plot.font_scale,title="Credit Card Balance Distribution by Gender")output=Embed(plot=plot,file_name="balance_distributions")()
print(output)
It looks like there are two populations for each gender. The larger one for both genders is centered near 0 and then both genders have a secondary population that carries a balance.
Encode the Gender
Since the Gender data is categorical we need to create a dummy variable to encode it. So what I'm going to do is encode males as 0 and females as 1 (because of the nature of binary encoding, we could swap the numbers and it would still work).
Since we encoded Male as 0 and Female as 1, when the gender is Male the second term drops out and all you have is \(\beta_0\), while for females you have have the full equation. How do you interpret the \(\beta\)s?
\(\beta_0\) is the average balance that males carry
\(\beta_0 + \beta_1\) is the average balance that females carry
\(\beta_1\) is the difference between the average balances
We can check this by comparing the coef entry in the summary table that I printed. The Intercept is \(\beta_0\) and gender is \(\beta_1\)
male_mean=data[data.Gender=="Male"].Balance.mean()female_mean=data[data.Gender=="Female"].Balance.mean()print(f"Average Male Balance: {male_mean:.7}")print(f"Average Female Balance: {female_mean:0.7}")print(f"Average difference: {female_mean-male_mean:0.7}")expect(math.isclose(male_mean,model.params.Intercept)).to(be_true)expect(math.isclose(female_mean-male_mean,model.params.gender)).to(be_true)
Average Male Balance: 509.8031
Average Female Balance: 529.5362
Average difference: 19.73312
I didn't set up a hypothesis test, but if you look at the p-value (the P>|t| column in the summary) for gender you can see that it's much larger than 0.05 or whatever level you would normally choose, so it's probable that gender isn't significant, so the average balance for both genders is really the same, given the deviation, but this is just about interpreting the coefficients, not deciding the validity of this particular model.
End
So there you have it. If you have the specialized case of binary categorical data you can convert the category to dummy variables and then fit a linear regression to it. If you encode the values as 0 and 1 then the y-intercept will give you the average output value for the category set to 0 and the slope will give you the difference between the average outputs for the categories. If you use different dummy variables the meanings will change slightly, although you will still be inferring things about the averages. Why is this interesting - predicting the mean for each category?
Logistic regression also relies on dummy variables for categorical encodings and this shows a preliminary step that helps us:
encode the dummy variables
build a linear model using statsmodels
view summary information about the model
I didn't emphasize it, but the p-value for the f-statistic might be valuable when deciding whether the categorical data is different enough to use as a feature.
James G, Witten D, Hastie T, Tibshirani R, editors. An introduction to statistical learning: with applications in R. New York: Springer; 2013. 426 p. (Springer texts in statistics).
Notes
Book site (includes link to PDF download of the book)
The first step of Clicker Training is "Get your rabbit to do what you want it to do", which seems a little ambiguous when you see it on the list, but it breaks down into four basic categories.

Lure With Food
If your rabbit will take food from your hand you can teach her to go places by having her follow your hand with food in it, although the next category - Follow a Target - is a preferable way to do this.
Follow a Target
Create a target (like a ping-pong ball on the end of a stick) and teach your rabbit to follow it.
Start by putting it near her and clicking when she touches it with her nose or mouth
Extend it slowly by moving it away from her and rewarding her when she follows it
Shaping
The target training follows the shaping pattern, wherein you start by rewarding anything that sort of looks like what you want her to do - like just looking at the target when you show it to her, then progressively extending the behavior needed until it's the one that you want. For example:
Go A, Bhayani R, Huang L. Twitter sentiment classification using distant supervision. CS224N project report, Stanford. 2009 Dec;1(12):2009.
Notes
This was a project report that looked at using emoticons to create a labeled data set for tweets.
About the Data
The authors noted that tweets are different from many other sources used for sentiment analysis - things like movie reviews - in that:
they are character limited (140 characters at the time of the paper, it has since doubled)
there is a huge amount of data to pull - and it is continuously being generated
there is an unusual amount of slang and non-normal spelling
it isn't subject specific - you can filter using the API, but twitter itself isn't a single-subject service
Using Emoticons as Labels
The use of emoticons to decide if a tweet is positive, or negative has the benefit of automatically creating a labled dataset, but since they are used as the labels they have to remove them from the training set, removing one of the more useful ways of identifying the tweet sentiment.
Getting and Cleaning the Data
The pulled 100 tweets form the API every 2 minutes until they had 800,000 positive and 800,000 negative tweets (after removing some tweets in pre-processing). The API lets you query by emoticon so the used ":)" to grab positive tweets (the API matches any known equivalent emoticon) and ":(" for negative tweets. They removed re-tweets and duplicates as well as any tweet that had both positive and negative emoticons in them. They then replaced usernames with the token USERNAME and URLs with URL and limited the number of consecutively repeated characters to 2.
Zhai C, Massung S. Text data management and analysis: a practical introduction to information retrieval and text mining. First edition. New York: Association for Computing Machinery; 2016. 510 p. (ACM books).
Sentiment Analysis is a part of Natural Language Processing that looks to transform freeform text into structured data. Opinion is an expression of belief, while sentiment is an expression of feeling. What is sometimes called Sentiment Analysis - the measurement of positive or negative sentiment of a text is really Polarity Classification, a subset of Sentiment Analysis. (Pozzi, Fersini, et al., 2017).


|
prometheus-client-c
0.1.0
Prometheus client for the C programming language
|
https://prometheus.io/docs/concepts/metric_types/#gauge More...
Go to the source code of this file.
Typedefs | |
| typedef prom_metric_t | prom_gauge_t |
| A prometheus gauge. More... | |
Functions | |
| prom_gauge_t * | prom_gauge_new (const char *name, const char *help, size_t label_key_count, const char **label_keys) |
| Returns a pointer to a prom_gauge. | |
| int | prom_gauge_destroy (prom_gauge_t *self) |
| Destroys a pointer to a prom_gauge. | |
| int | prom_gauge_inc (prom_gauge_t *self, const char **label_values) |
| Increment the prom_gauge by 1. | |
| int | prom_gauge_dec (prom_gauge_t *self, const char **label_values) |
| Descrement the prom_gauge by 1. | |
| int | prom_gauge_add (prom_gauge_t *self, double r_value, const char **label_values) |
| Add the value to the prom_gauge. | |
| int | prom_gauge_sub (prom_gauge_t *self, double r_value, const char **label_values) |
| Subtract the value from the prom_gauge. | |
| int | prom_gauge_set (prom_gauge_t *self, double r_value, const char **label_values) |
| Set the value for the prom_gauge. | |
| typedef prom_metric_t prom_gauge_t |


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--- layout: article title: Onslaught! Arena now on sale for $1.99 author: matt tags: [onslaughtarena] ---
Happy new year! Our first game Onslaught! Arena launched exactly one month ago today, so we're pretty excited about this year. To welcome 2011, we're having a 60% off sale! You can buy Onslaught! Arena now from the Chrome Webstore for just $1.99.
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Have you ever heard the popular saying “Like owner, like a dog”? Well, this saying is absolutely true and we have got some pictures to prove it. This fun picture series of dogs and owners is created by British photographer Gerrard Gethings. He is a famous photographer and is known for his funny dog portraits. The best thing about the portraits is that they are so full of life and energy.
But for his recent project, Gethings thought of doing something different and unique. That’s why he has paired the owner and dog together to show their similar appearance traits. This picture series is so amazing. All thanks to Gethings's hard work, talent, skill, and patience that makes each of these pictures different and funnier than others.
Scroll down to check out the pictures. And don’t forget to tell us which one of these pictures you liked the most in the comments section.
#1 Benji & Harper (Schnoodle)
#2 Sergei & Spike (Siberian Husky)
#3 François & Antoine (French Bulldog)
#4 Harry & Hattie (Italian Spinone)
#5 Henry & Hope (Afghan Hound)
#6 Jessica & Buddy (Bishon Frise)
#7 Cenk & Horst (Schnauzer)
#8 Elle And Yasmin Le Bon (Puli)
#9 Monica & Reggie (Chow Chow)
#10 Charlotte & Caspar (Chinese Crested)


| Name: mrs sharada | Reg No: 4-6smhc17 |
|---|---|
| Age / Sex:30 yrs | Contact No: |
| Marital Status:ml10 years | Date:28/6/17 |
| Occupation:housewife. | Dr. |
| Address: | DIAGNOSIS- |
Thyroid dysfunction since 8 years. Wt.gain irregularity in periods and hairfall so went to gynaec and then got diagnosed with hypothyroidis.
Lmp: 7/6/17 4th day onwards inc flo 1st day only spotting.8 day s flo. From 2 yeasr post ivf heavybleeding. Took homoeo now controlled. Ultroxin 125 mg.
Wd b4 menses 2 weeks befr
Swelling fingers since 8 years.
Pain started from 8 years<cold, early mng >sun rise., pressing interphalangeal muscles.
Dark circles dark pigmentation in folds.
Aversion milk and spicy food.
From 5 years groundnut and banana distension in abd with nausea.
Again chikki is fine . cant eat plain groundnut,
Wanted to learn dance bt due to finances left. Now likes to watch.
Doesn’t like to b alone.wants company. Keeps tv on wne alone to feel som one ther.
Post accident fear.
Fear cockroaches n darkness.
Craving fr limestone.
Rx: calc iod 30 bd
Thyr 6x qid
Acon 7 doses alt days.
6/9/17: lmp: 5/9/17; 15/7/17. Less bleeding. Joints pain elbow and knees. Must take calcium and d3. Craving for limestone.  Sleep is good. Snoring is there. Feeling hungry.
Rx:
1. Calc.carb 200 – 4 doses – thu/mon.
2. sil 30 qid
3.cal.phos 30 qid.
28/9/17: PAIN IN THE KNEE JOINT PAIN REDUCED AND ELBOW STILL THER. LMP:5/9/17. SWELLING OF FINGERS SAME. NO PAIN.CRAVING FR LIMESTONE REDUCING. FIRST GOT PAIN TO LEFT KNEE THN KNEEJOINT THEN ELBOW JOINT. PIMPLES COMING FRM 3 MONTHS. WHENEVR CHANGES PLACE TO NOEW PLACE GETS THIS PIMPLES. NIGHT GETS LEG PAIN PULLING PAIN. <AS SOON AS SHE GETS ONTO BED AFTER 5 MIN WILL GET PAIN THEN REDUCES AFTER 15 MIN WEN SHE GETS SLEEP FROM 6-7 YEARS. QUALITY OF SLEEP IMPROVED. HAIRLOSS ALSO REDUCED. WHETHER MUST BE COLD BUT SHE SHD BE WARM.
RX:
CALC CARB 200 – 2 DOSE WATER
RHUS TOX 30 – DISC BID WATER
MAG PHOS 12 X – QID 2 BOTTLES.
SULPHUR 200 – 1 DOSE NOW.
2/11/17: pain in the anl region frm 4 days. 3 times motions. Normal stool. Burning anus. <during stool. Body pain since weather change. feet pain <lying. Pulling type of pain. >stretch. Craving for limestone returns.elbow joing and knee joint pain mostly better. Dandruff more. Haifall no firther improvement.from 10 days getting headache had some reltives also frm a week. Root of the nose and one sided pain. lmp: 12/10/17.normal.
Rx:
1.calc carb 1m – 3 doses – 5 days once
2. rhus tox 200 disc bd
3. thyroidinum 3x bd
4. ferr.phos 6x 4-4-4-4
9/12/17: lmp: 12/10/17 then got today. More work means gets pain otherwise compared to before very less.  Use to have earlier more burning urination , white discharge, throat infections. But coming to blore no pbms since then. Craving for limestone persists. Marriage time very thin. Swelling fingers didn’t reduce. Better walking.
Rx:
Ferr.phos 12x 4-4-4-4 small bottle.disc.
Calc.iod 30 – pills 1 dram 4-0-4 b/food.
Rubrum 7 doses – 1 night b/food.
Mag phos1m menses pain sos.
Calcareacarb 1m+ferr met 1m+medo 1m- 1 dram pills 4-4-4-4 for 4 days.
14/12/17:
Syp. Alfalfa avena drops.
30/12/17: 26/12/17. Lmp. Now clotted bleeding from 2 days. 22nd had one day bleeding.
Rx:
Millifolium 200 +sabina200 +cimicifuga 200 +mag phos 200 – 2 dram pills 4-4-4-4-4 5 days.
5/1/18: 4 pads mus change per day. Clots reduced but cont bleeding.
Pain in the back region. Light weakness at times.
Rx:
milliefolium 1m +calc carb1m + china 1m – 4-4-4-4 for 5 days.
8/1/18: bleeding not stopped.
Rx:
Sabina 1m 1 dram pills – 2 hourly.
Phos 10 m – 1 dose stat .
Carc1m – 1 dose tomo mng.
10/1/18:
Vomiting sensation . clots. Dark maroon. 25 % better than before after new med. Mild itching due to pads.
Rx:
Phos 10 m – 1 dose stat.
Bell1m+sabina1m+carc1m 4 pills 2 hourly.
After bleeding stops then:
Puls 10m – 1 dose mng b/brush water
Ferr met 200 – disc 4-0-4
Thlaspi b pastoris Q 15-0-10 – 15 drops a/food.water
Rub 15 – 1 night b/food.
2/2/18: hb 6%. Feeling sleepy, climbing stairs finds breathlessness, yday gave ferr met 1m one dose . feels a bit better after that.
Thyroidinum 1m – 2 doses 3 days once b/brush water.
Bell 1m – 3 doses alt day b/brush water.
Lecitihin 30 -4-4-4-4 disc.
Ferr met 1m – 2 doses 3 days once b/brush water.
Thalaspi b p Q 10-10-10-10 drops a/food. Water.
17/2/18: weakness better. Trembling better. From yday slight spotting seen all the prev said complaints are better.lmp: 26th December. Mild pain in the low back and low abd pain. feeling scared that period is coming again that till jan 25th she was bleeding and again started now. Feeling more thirsty thse days frm a week. Feeling a bit body pain for slight exertion also. But still wants fan during sleep. Likes hot food. Weather must be moderate. loss of interest in coition says feeling tired and sleepy or lazy to act.
Rx:
sulphur 1m – 1 dose b/food water.
Crocus sativus 200 – 1 dose b/brush.
Ustilago 30 disc 3—3-3-3.
Acid phos 1m 15 – 1 dose night b/food with water.
23/2/18: 19th night bleeding. 22 spotting . today spotting. Weakness from today. Pressing pain either sides of sternum. Mixing anything feels pain. craving more for stone.
Rx:
3 doses – crocus sativus 1m – 1-1-1.
10/3/18: 2 DAYS BACK GOT SPOTTING AND GOT CLOT AND THEN STOPPED. CRAVING FR STONE REDUCED. FEELING MORE SLEEPY. NIGHT WHEN SLEEPING LEGS PULL. FEELING HOT. GOT BLEEDING PER RECTUM 8TH NIGHT.
RX:
CALC CARB 10 M – 1 DOSE
RHUS TOX 1M 4-4-4-4 1 DRAM
29/3/18: 25/3/18 – LMP. LITTLE ONLY BLEEDING. PAIN IN THE LEGS. BODY PAIN AND FINGER PAINS AND SWEELING JOINT PAIN. PERIOD BEFORE AND AFTER ALSO GETTING PAIN NOW. TAKING 150MG OTHERWISE FEELING VERY SLEEPY. REDUCING. 1ST DAY ONLY GOT WATER THIN BLEEDING.
RX:
PULSATILLA 200 – DISC 3-3-3-3
CROCUS SATIVUS 200 DISC 3-3-3-3
FOLLICULINUM 200 DISC 3-3-3-3
MAG PHOS 12 X 4 TABS 1 HOURLY.
4/5/18: lmp: 25/3/18 after 10 days reduced. If works more spotting. Lmp: 23/4/18 from 25th more bleeding and more clots. Today only feels reduced.
Rx:
Crocus sativus 1m + carcinosin 1m+ tbp1m – 4-4-4-4 1 dram pills.
Thyroidinum 1m – 3 doses daily 1 dose night b/food.
29/5/18: LMP: 29/5/18 FRM MORNING.
2/6/18: mng 11-12 evening 7-9 clots more. 2 pads per day. Back pain low. 5th day today. Dark color clots. From 3 years neck blackish. Burning. If sleeps well will feel better.
Rx:
Bell1m – 2 dram pills – 2 hourly.
15/6/18: AFTER A WEEK TAKING GYNAE CVP THE BLEEDING STOPPED.
CROCUS SATIVUS 1M – 4-4-4-4. 1 DRAM PILLS
SEC COR 1M – 4-4-4-4. 1 DRAM PILLS
BELL1M – 4-4-4-4.
RUB 15 – NT 1 DOSE.
6/7/18: pain in the rt.side of neck inbetewwn the strnocleido mastoid angle. Wounded pain. medial and lateral and middle fingers on the feet itching is there. Hairfall. Weekly once headache. < headbath.
Rx:
Ignatia 1m –2 dose – mng b.food.weekly b.food
Ferr phos 200 – 4-4-4-4.
Rubrum 15 doses 1 nt b food.
r.a 2 weeks.
24/7/18: lmp: 8 /7/18 bleeding started heavily from 16th july.
Rx:
Ustilago1m 4pills 30 min once with water.
7/8/18: lump in the left breast . painful at times. 2 weeks only got formed. Smelly mild white discharge. No desire. Headache more these days. Mood swings felt like crying and cried a lot. Dreams like day events. Itching body reduced.
Rx:
Thyroid 1m / calcarea carb 1m / sulphur1m.- 4-4-4-4. 2 dram pills alternate weeks.
Bell1m/ustilago1m –4 pills sos. Heavy bleeding. 4 pills 3 hourly.
Milliefolium1m – 5th day – 4 pills 3 hourly.
Rub 30 – night 1 dose.
Lecithin 200 – 4-0-4 disc.
27/8/18: frm sat 25. Had white discharge till she had period and then gone.
Rx: 1 ) pulsatilla 1m – 1 dram pills.
4/9/18: bleeding big clots.
Rx:
1.thlaspi b p 1m/sec cor1m/-
7/9/18: bleeding not stopped clotted and heavy during afternoon. Feeling low depressed and want air, cold, feeling hot inside and out. no app.
Rx:
Ac.phos 30+china30 disc 4-4-4-4
Actae racemosa or cimicifuga 30 /stram1m – 4-pills hourly fr today tomorrow 2 hourly.
20/9/18:
Past h/o:
Got herpes on backbone – inter 1st year.
An year severe fever 15 days and had a lot of weakness hairfall.
Weakness before menarche. Legs pain constantly. Legs use to pain constantly. After menarche better with that.
Never had mothers milk.
Doesn’t like eggs.
Towards spicy.
No colas and chocolates.
11/11/18:
Bleeding stopped after lyco and phos.
Dry cough more in the night.
Rx:
Sepia 200 – 4 pills 3 hourly.
3/12/18: last night nb, throat burning, blocks in the night. Had a quarrel and she cried a lot. Nasal mucus yellowish. Night reeling and vomiting sensation since 3 days. Frequent urine maybe frm 5 days.
Rx:
Nux vom 200 – 4-4-4-4
Lyco 200 – 4-4-4-4.
7/12/18: headache frequent. Had an ep of cough cold etc. feeling very hot these days. If switches on fan cold.
Rx:
Alfa+avena – 10-10-10-10 drops a/food water.
15/12/18: WEAKNESS. BLOATING. GASTRITIS.
RX:
NAT PHOS 12 -4-4-4-4.
17/12/18: nausea. Giddiness from 3-4 days.
Rx:
nm200 – 3 doses night b/food.
Thyroidinum 1m – 3-0-3 a/food.
Rub 15 – 1 dose night b/food.
2/1/18: bloating. Headache. Able to walk well. Cold thick yellow. Mng more. Hairfall. Dandruff.
Rx:
staphysagriaQ- 15 ml in 100ml oil.
Carc 1m – 4 pills 3 hourly.
Sepia 200 – 3 doses – water 3 hourly.
7/1/19: white discharge. No period still.
Rx:
lach 1m – 1 dose.
Apis 30 4-4-4 water.
Ustilago1m,bell1m,sabina1, thlaspi bursa pastoris1m, sec cor 200. Mag phos1m – pain sos.
22/1/19:
DIN GET PERIODS YET. HEADACHE HAS INCREASED. PAIN ONE SIDE INSIDE THE EYE. LOT OF HEADACHE. SWELLING. IF SKIPS FOOD.
RX:
CALC CARB 1M – 3 DOSES. 1 DOSE WITH WATER. REPEAT DAILY MNG B/FOOD.
1/2/19:
RX: REFER NOTES
LYCO 1M – 1 DOSE.
PULS 0/1 – 2-2-2 WATER FR A WEEK,
RUB 15 – 1 NIGHT B/FOOD.
LECITHIN 200- 4-0-4. DISC.
8/2/19: spotting lmp: 8/2/19.
Rx:
Bry1m – 4-4-4.
18/2/19: spotting seen itll 12/2/19. After tht feels energetic. No other complaints. Had occipital headache and rt.side neck pain. has body pains also frm mng.
Rx:
Lyco 1m – dose.
Lachesis 1m 5 days later another dose.
Gels 200 – pills 4-4-4-4. 3 days. 1dram.
4/3/19: 24 ONWARDS OF FEB FEELS BLEEDING IS MORE. AFTER 12TH SPOTTING STARTED ON 21ST.BUILDING THE FLOW FRM 24TH TILL NOW.
RX:
ANT TART 200 – 4-4-4-4
12/3/19: STOPPED PERIOD ON 10TH MORNING. TODAY WHEN EXERCISING SPOTS OF BLOOD SEEN. TSH: 6.79 UI/DL. HB: 14.4GM. WHILE EXCERCISING FEELS GOOD. HEADACHES IF SKIPS BREAKFAST. FEELS BLEEDING IS THERE NOW. FEELING EYES ARE BECOMING RED THESES DAYS. R BURNING. NOT GETTING SLEEP WELL FEELING DISTURBED. GETTING AWAKE AFTER SMALL SOUND AND NOT GETTING SLEEP AFTER THT. HAIR IS FALLING IMMENSELY.
RX:
MEDO 1M - 1 DOSE .
ANT TART1M – 4-4-4-4.
22/3/19: bleeding stopped for previous med. Hairfall better.itching of skin after sex. Reduces in 10 min. only on hands. Neck. Headaches not there.
Aversion to milk
Childish gestures
Stubborn
Rx:
X-ray 1m – 1 dose.
Nat carb 1m – 4-4-4-4
Silicea 1m – 4-4-4-4.
Thyroidinum1m- disc 4-0-4.
Rub 15 days – 1 tab night b/food.
25/4/19: more headaches. Feels gassy and headaches. Not feeling comfortable in stomach. Leg pain.
Gossypium Q – 15-15-15-15 drops a/food water.
Apis1m/puls1m – 4-4-4-4 b/food.
27/4/19: eructations more. Unable to digest food. Sour eructations.
Rx:
Nat phos 200 – 4-4-4-4.
6/5/19: feeling breast left pain at times right. Lmp:
Rx:
Kali brom 200 – 1 dose.
Nat phos 1m - 1 dose mng on the 1st day of menses.
20/5/19: lmp: 13/5/19 spoting from 16th flow. Pain only when clots but bearable. Weak feeling. Dull and moody. With husband having respiratory pbm he is showing more effect irritation on her. 2 pads /day. Heaviness in abdmen.
Rx:
China /acid phos1m.
Ferr met 200.
23/5/19: bleeding increased. Clots. Only daytime. 2-3 /day. Tiredness. Heaviness body.
Rx:
bell1m/viburnum opulus 200-4 pills 2 hourly.
China1m/ferr met 1m/acid phos 1m – 4-4-4-4.
4/6/19: 29TH THE BLEEDING HAS STOPPED. THROAT INFECTION. BODY PAINS. CHILLS. GASSY ABDOMEN. AT HOME MOTHER IN LAWS DEATH CEREMONY. SO AFTER THT STRAIN.
RX:
FIRST 5 DAYS:
HEPAR SULPH1M – 4-4-4-4.
BELL200/GELSIMIUM200/ARS200 – 4-4-4-4.
ALSPETOL 25 – 25-25- 25 DROPS A/FOOD.
AFTER 5 DAYS
OOPHORINUM1M – 4-4-4
NAT CARB 1M – 4 MNG/EVEING.
CAPSICUM 1M – 4 AFTN/NIGHT.
RUBRUM – 1 TAB 15 NIGHT.
12/6/19: LMP: 10/6/19. CLOTS AND STRINGY.
RX:
IGNATIA1M – 1 DOSE. 4 PILLS. REPEAT 3 HOURLY.
17/6/19: increased flow. Painless. Clots,thick marronish, continuous flow. 3 pads /day. Xl pads. Itching vulval region. When clots are coming feels backpain. But feeling better sleep. Heavy work after only flow is more. Lmp: 10/6/19.
Rx:
bell1m/viburnum opulus 200-4 pills 2 hourly.
China1m/ferr met 1m/acid phos 1m – 4-4-4-4.
Sodhari 2-2-2 tsp a/food.
27/7/19: 7th spotting. Lmp: 12/07/19 till 25th of July. Headache is frequent these days. Gastritis like if drinks tea or eating outside. Fullness of abdomen and flatulence is more. One sided headache. Got throat inf in tour once and it reduced after homoeo sos given to her long back.
Rx:
Nat phos 1m/ – mng 4 pills
Lachesis 1m – aftn 4 pills
Sil 12x 4-4-4-4
Oophorinum1m/folliculinum1m – night 4 pills b/food
Lyco 200 – 1 dose b/brush mng.


About Me
- Experienced Mechatronics Engineer and Electronics Technician with a demonstrated history of working in the Industrial maintenance.
- Skilled in Engineering, Power Electronics , Electrical Drive, Programmable logic controllers and Industrial Electronics also i am skilled in Python (Programming Language), Artificial Intelligence, Machine Learning, Deep Learning and Reinforcement Learning.
- Strong Engineering Skills with a Diploma of Industrial Electronics Engineering from Wadi Al-Seer Training Collage and Bachelor's of Mechatronics Engineering from Al Balqa Applied University
- I have some goals Creating A personal Blog About AI and deploy my projects in AI i hope it will be soon.